09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Apparatus for recording, transmission, manipulation, compression, enhancement, or reproduction of signals, including video, sound, or images; Computer software: Software for signal processing, specifically video, still imaging, and audio; Artificial intelligence software; Machine learning software; Image management software; Computer software, including downloadable software for use in sensor data analysis, including event sensors, digital photography, digital videography, infra-red, multispectral imaging, audio, and radio signals, namely, for analysis, categorization, object recognition, compression, enhancement, editing, and manipulation; Computer hardware: central processing units, graphic processing units, system on a chip, integrated circuits, multiprocessor chips, ASIC, for use in sensor data capture and analysis, including event sensors, digital photography, digital videography, infra-red, multispectral imaging, audio, radio signals, namely, for analysis, categorization, object recognition, compression, enhancement, editing, and manipulation. Software as a service; Platform as a service; Design and development of software and hardware, including compilers, for use in sensor data capture and analysis, including event sensors, digital photography, digital videography, infra-red, multispectral imaging, audio, radio signals, namely, for analysis, categorization, object recognition, compression, enhancement, editing, and manipulation.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Apparatus for recording, transmission, manipulation, compression, enhancement, or reproduction of signals, including video, sound, or images; Computer software, namely, software for signal processing, specifically video, still imaging, and audio; Artificial intelligence software; Machine learning software; Image management software; Computer software, including downloadable software for use in sensor data analysis, including event sensors, digital photography, digital videography, infra-red, multispectral imaging, audio, and radio signals, namely, for analysis, categorization, object recognition, compression, enhancement, editing, and manipulation; Computer hardware, namely, central processing units, graphic processing units, system on a chip, integrated circuits, multiprocessor chips, ASIC for use in sensor data capture and analysis, including event sensors, digital photography, digital videography, infra-red, multispectral imaging, audio, radio signals, namely for analysis, categorization, object recognition, compression, enhancement, editing, and manipulation Software as a service; Platform as a service; Design and development of software and hardware, including compilers, for use in sensor data capture and analysis, including event sensors, digital photography, digital videography, infra-red, multispectral imaging, audio, radio signals, namely for analysis, categorization, object recognition, compression, enhancement, editing, and manipulation
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Apparatus for recording, transmission, manipulation, compression, enhancement, or reproduction of signals, including video, sound, or images; Computer software: Software for signal processing, specifically video, still imaging, and audio; Artificial intelligence software; Machine learning software; Image management software; Computer software, including downloadable software for use in sensor data analysis, including event sensors, digital photography, digital videography, infra-red, multispectral imaging, audio, and radio signals, namely, for analysis, categorization, object recognition, compression, enhancement, editing, and manipulation; Computer hardware: central processing units, graphic processing units, system on a chip, integrated circuits, multiprocessor chips, ASIC, for use in sensor data capture and analysis, including event sensors, digital photography, digital videography, infra-red, multispectral imaging, audio, radio signals, namely, for analysis, categorization, object recognition, compression, enhancement, editing, and manipulation. Software as a service; Platform as a service; Design and development of software and hardware, including compilers, for use in sensor data capture and analysis, including event sensors, digital photography, digital videography, infra-red, multispectral imaging, audio, radio signals, namely, for analysis, categorization, object recognition, compression, enhancement, editing, and manipulation.
A vehicle cabin monitoring system includes a customization profile for storing: annotated images associated with annotation(s) indicating a ground truth for an associated region of an image; and a plurality of core processing parameters for an image processing component of an image processor. The system is: responsive to user interaction with a user interactive control of the vehicle within a field of view of a camera for storing an image acquired by the camera at the time of interaction in the customization profile with an annotation indicating a ground truth for an associated region of the image according to the interaction; and configured to use images from the customization profile for re-training an image processing component of the processor and for storing updated core processing parameters produced by the re-training in the customization profile for use by the re-trained image processing component in processing subsequently acquired images.
G06V 20/59 - Contexte ou environnement de l’image à l’intérieur d’un véhicule, p.ex. concernant l’occupation des sièges, l’état du conducteur ou les conditions de l’éclairage intérieur
G06V 10/25 - Détermination d’une région d’intérêt [ROI] ou d’un volume d’intérêt [VOI]
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 40/10 - Corps d’êtres humains ou d’animaux, p.ex. occupants de véhicules automobiles ou piétons; Parties du corps, p.ex. mains
5.
Methods And Systems to Predict Activity In A Sequence Of Images
A method to determine activity in a sequence of successively acquired images of a scene, comprises: acquiring the sequence of images; for each image in the sequence of images, forming a feature block of features extracted from the image and determining image specific information including a weighting for the image; normalizing the determined weightings to form a normalized weighting for each image in the sequence of images; for each image in the sequence of images, combining the associated normalized weighting and associated feature block to form a weighted feature block; passing a combination of the weighted feature blocks through a predictive module to determine an activity in the sequence of images; and outputting a result comprising the determined activity in the sequence of images.
G06V 10/75 - Appariement de motifs d’image ou de vidéo; Mesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexte; Sélection des dictionnaires
G06V 20/30 - RECONNAISSANCE OU COMPRÉHENSION D’IMAGES OU DE VIDÉOS Éléments spécifiques à la scène dans les albums, les collections ou les contenus partagés, p.ex. des photos ou des vidéos issus des réseaux sociaux
G06F 18/22 - Critères d'appariement, p.ex. mesures de proximité
G06F 18/214 - Génération de motifs d'entraînement; Procédés de Bootstrapping, p.ex. ”bagging” ou ”boosting”
G06F 18/2113 - Sélection du sous-ensemble de caractéristiques le plus significatif en classant ou en filtrant l'ensemble des caractéristiques, p.ex. en utilisant une mesure de la variance ou de la corrélation croisée des caractéristiques
A method at a first participant's client conferencing system in a videoconference comprises receiving, from a second client conferencing system, at least one first video frame of a first video signal including an image of the second participant looking at a third participant, and first metadata associated with the first video frame and including an identity of the third participant. The image of the second participant is modified in the first video frame so that the first video frame is displayed on a first area of the client conferencing system with the second participant looking at a second area of the first display configured for displaying a second video signal of the third participant identified by the first metadata.
A vehicle occupant monitoring system, OMS, comprises an image acquisition device with a rolling shutter image sensor configured to selectively operate in either: a full-resolution image mode where an image frame corresponding to the full image sensor is provided; or a region of interest, ROI, mode, where an image frame corresponding to a limited portion of the image sensor is provided. An object detector is configured to receive a full-resolution image from the image sensor and to identify a ROI corresponding to an object of interest within the image. A controller is configured to obtain an image corresponding to the ROI from the image sensor operating in ROI mode, the image having an exposure time long enough for all rows of the ROI to be illuminated by a common pulse of light from at least one infra-red light source and short enough to limit motion blur within the image.
G06V 10/143 - Détection ou éclairage à des longueurs d’onde différentes
G06V 10/147 - Caractéristiques optiques de l’appareil qui effectue l’acquisition ou des dispositifs d’éclairage - Détails de capteurs, p.ex. lentilles de capteurs
G06V 10/25 - Détermination d’une région d’intérêt [ROI] ou d’un volume d’intérêt [VOI]
G06V 10/60 - Extraction de caractéristiques d’images ou de vidéos relative aux propriétés luminescentes, p.ex. utilisant un modèle de réflectance ou d’éclairage
G06V 20/59 - Contexte ou environnement de l’image à l’intérieur d’un véhicule, p.ex. concernant l’occupation des sièges, l’état du conducteur ou les conditions de l’éclairage intérieur
G06V 10/98 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos Évaluation de la qualité des motifs acquis
An image processing system comprising a processer configured to receive a sequence of images frames from an image acquisition device and configured to: analyze at least a currently acquired image frame to determine if activity is occurring in an environment with a field of view of the image acquisition device; responsive to analyzing a subsequent image frame acquired after the currently acquired image frame and determining that no activity is occurring in the environment, retrieve an image frame acquired before the currently acquired image frame which has been analyzed and where it has been determined that no activity is occurring in the environment; analyze the subsequent image frame and the retrieved image frame to identify a state of one or more objects within the field of view of the image acquisition device; and responsive to a change in state of the one or more objects, notify a user accordingly.
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p.ex. des objets vidéo
A method for identifying a gesture from one of a plurality of dynamic gestures, each dynamic gesture comprising a distinct movement made by a user over a period of time within a field of view of an image acquisition device comprises iteratively: acquiring a current image from said image acquisition device at a given time; and passing at least a portion of the current image through a bidirectionally recurrent multi-layer classifier. A final layer of the multi-layer classifier comprises an output indicating a probability that a gesture from the plurality of dynamic gestures is being made by a user during the time of acquiring the image.
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 40/20 - Mouvements ou comportement, p.ex. reconnaissance des gestes
A method for monitoring occupants of a vehicle comprises identifying a respective body region for one or more occupants of the vehicle within an obtained image; identifying within the body regions, skeletal points including points on an arm of a body; identifying one or more hand regions; and determining a hand region to be either a left or a right hand of an occupant in accordance with its spatial relationship with identified skeletal points of the body region of an occupant. The left or right hand region for the occupant are provided to a pair of classifiers to provide an activity classification for the occupant, a first classifier being trained with images of hands of occupants in states where objects involved are not visible and a second classifier being trained with images of occupants in the states where the objects are visible in at least one hand region.
G06V 20/59 - Contexte ou environnement de l’image à l’intérieur d’un véhicule, p.ex. concernant l’occupation des sièges, l’état du conducteur ou les conditions de l’éclairage intérieur
G06V 40/10 - Corps d’êtres humains ou d’animaux, p.ex. occupants de véhicules automobiles ou piétons; Parties du corps, p.ex. mains
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
A method for calibrating a vehicle cabin camera having: a pitch, yaw and roll angle; and a field of view capturing vehicle cabin features which are symmetric about a vehicle longitudinal axis comprises: selecting points from within an image of the vehicle cabin and projecting the points onto a 3D unit circle in accordance with a camera projection model. For each of one or more rotations of a set of candidate yaw and roll rotations, the method comprises: rotating the projected points with the rotation; flipping the rotated points about a pitch axis; counter-rotating the projected points with an inverse of the rotation; and mapping the counter-rotated points back into an image plane to provide a set of transformed points. A candidate rotation which provides a best match between the set of transformed points and the locations of the selected points in the image plane is selected.
A method for calibrating a vehicle cabin camera having: a pitch, yaw and roll angle; and a field of view capturing vehicle cabin features which are symmetric about a vehicle longitudinal axis comprises: selecting points from within an image of the vehicle cabin and projecting the points onto a 3D unit circle in accordance with a camera projection model. For each of one or more rotations of a set of candidate yaw and roll rotations, the method comprises: rotating the projected points with the rotation; flipping the rotated points about a pitch axis; counter-rotating the projected points with an inverse of the rotation; and mapping the counter-rotated points back into an image plane to provide a set of transformed points. A candidate rotation which provides a best match between the set of transformed points and the locations of the selected points in the image plane is selected.
A method comprises displaying a first image acquired from a camera having an input camera projection model including a first focal length and an optical axis parameter value. A portion of the first image is selected as a second image associated with an output camera projection model in which either a focal length and/or an optical axis parameter value differ from the parameters of the input camera projection model. The method involves iteratively: adjusting either the focal length and/or an optical axis parameter value for the camera lens so that it approaches the corresponding value of the output camera projection model; acquiring a subsequent image using the adjusted focal length or optical axis parameter value; mapping pixel coordinates in the second image, through a normalized 3D coordinate system to respective locations in the subsequent image to determine respective values for the pixel coordinates; and displaying the second image.
A method for correcting an image divides an output image into a grid with vertical sections of width smaller than the image width but wide enough to allow efficient bursts when writing distortion corrected line sections into memory. A distortion correction engine includes a relatively small amount of memory for an input image buffer but without requiring unduly complex control. The input image buffer accommodates enough lines of an input image to cover the distortion of a single most vertically distorted line section of the input image. The memory required for the input image buffer can be significantly less than would be required to store all the lines of a distorted input image spanning a maximal distortion of a complete line within the input image.
Disclosed is a multi-modal convolutional neural network (CNN) for fusing image information from a frame based camera, such as, a near infra-red (NIR) camera and an event camera for analysing facial characteristics in order to produce classifications such as head pose or eye gaze. The neural network processes image frames acquired from each camera through a plurality of convolutional layers to provide a respective set of one or more intermediate images. The network fuses at least one corresponding pair of intermediate images generated from each of image frames through an array of fusing cells. Each fusing cell is connected to at least a respective element of each intermediate image and is trained to weight each element from each intermediate image to provide the fused output. The neural network further comprises at least one task network configured to generate one or more task outputs for the region of interest.
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
G06V 10/80 - Fusion, c. à d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
G06V 20/59 - Contexte ou environnement de l’image à l’intérieur d’un véhicule, p.ex. concernant l’occupation des sièges, l’état du conducteur ou les conditions de l’éclairage intérieur
The technology relates to tuning a data translation block (DTB) including a generator model and a discriminator model. One or more processors may be configured to receive training data including an image in a second domain. The image in the second domain may be transformed into a first domain with a generator model. The transformed image may be processed to determine one or more outputs with one or more deep neural networks (DNNs) trained to process data in the first domain. An original objective function for the DTB may be updated based on the one or more outputs. The generator and discriminator models may be trained to satisfy the updated objective function.
G06F 18/21 - Conception ou mise en place de systèmes ou de techniques; Extraction de caractéristiques dans l'espace des caractéristiques; Séparation aveugle de sources
A method of producing an image frame from event packets received from an event camera comprises: forming a tile buffer sized to accumulate event information for a subset of image tiles, the tile buffer having an associated tile table that determines a mapping between each tile of the image frame for which event information is accumulated in the tile buffer and the image frame. For each event packet: an image tile corresponding to the pixel location of the event packet is identified; responsive to the tile buffer storing information for one other event corresponding to the image tile, event information is added to the tile buffer; and responsive to the tile buffer not storing information for another event corresponding to the image tile and responsive to the tile buffer being capable of accumulating event information for at least one more tile, the image tile is added to the tile buffer.
H04N 5/335 - Transformation d'informations lumineuses ou analogues en informations électriques utilisant des capteurs d'images à l'état solide [capteurs SSIS]
A method to determine activity in a sequence of successively acquired images of a scene, comprises: acquiring the sequence of images; for each image in the sequence of images, forming a feature block of features extracted from the image and determining image specific information including a weighting for the image; normalizing the determined weightings to form a normalized weighting for each image in the sequence of images; for each image in the sequence of images, combining the associated normalized weighting and associated feature block to form a weighted feature block; passing a combination of the weighted feature blocks through a predictive module to determine an activity in the sequence of images; and outputting a result comprising the determined activity in the sequence of images.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
19.
Method and system to determine the location and/or orientation of a head
A method for determining an absolute depth map to monitor the location and pose of a head (100) being imaged by a camera comprises: acquiring (20) an image from the camera (110) including a head with a facial region; determining (23) at least one distance from the camera (110) to a facial feature of the facial region using a distance measuring sub-system (120); determining (24) a relative depth map of facial features within the facial region; and combining (25) the relative depth map with the at least one distance to form an absolute depth map for the facial region.
A method for producing a textural image from event information generated by an event camera comprises: accumulating event information from a plurality of events occurring during successive event cycles across a field of view of the event camera, each event indicating an x,y location within the field of view, a polarity for a change of detected light intensity incident at the x,y location and an event cycle at which the event occurred; in response to selected event cycles, analysing event information for one or more preceding event cycles to identify one or more regions of interest bounding a respective object to be tracked; and responsive to a threshold event criterion for a region of interest being met, generating a textural image for the region of interest from event information accumulated from within the region of interest.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
21.
METHOD AND SYSTEM TO DETERMINE THE LOCATION AND/OR ORIENTATION OF A HEAD
A method for determining an absolute depth map to monitor the location and pose of a head (100) being imaged by a camera comprises: acquiring (20) an image from the camera (110) including a head with a facial region; determining (23) at least one distance from the camera (110) to a facial feature of the facial region using a distance measuring sub-system (120); determining (24) a relative depth map of facial features within the facial region; and combining (25) the relative depth map with the at least one distance to form an absolute depth map for the facial region.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
22.
System and methods for calibration of an array camera
Systems and methods for calibrating an array camera are disclosed. Systems and methods for calibrating an array camera in accordance with embodiments of this invention include the capturing of an image of a test pattern with the array camera such that each imaging component in the array camera captures an image of the test pattern. The image of the test pattern captured by a reference imaging component is then used to derive calibration information for the reference component. A corrected image of the test pattern for the reference component is then generated from the calibration information and the image of the test pattern captured by the reference imaging component. The corrected image is then used with the images captured by each of the associate imaging components associated with the reference component to generate calibration information for the associate imaging components.
H04N 13/282 - Générateurs de signaux d’images pour la génération de signaux d’images correspondant à au moins trois points de vue géométriques, p.ex. systèmes multi-vues
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
G06T 7/80 - Analyse des images capturées pour déterminer les paramètres de caméra intrinsèques ou extrinsèques, c. à d. étalonnage de caméra
H04N 17/02 - Diagnostic, test ou mesure, ou leurs détails, pour les systèmes de télévision pour les signaux de télévision en couleurs
A video super resolution method comprises successively executing instances of a first plurality of layers (SISR) of a neural network for generating a first image (St) at a higher resolution than an input image frame (Xt); successively executing a second plurality of layers (VSR) of the neural network for generating a second image (Vt) at the higher resolution, at least one of the second plurality of layers generating intermediate output information (Ht), the second plurality of layers taking into account an output image (Yt−1) at the higher resolution generated by a previous instance of the network from a previous input image frame (Xt−1) and intermediate output information (Ht−1) generated by the second plurality of layers of the previous instance, and executing a third plurality of layers for combining the first (St) and second (Vt) images to produce an output image (Yt) for the instance of the network.
A device, such as a head-mounted device (HMD), may include a frame and a plurality of mirrors coupled to an interior portion of the frame. An imaging device may be coupled to the frame at a position to capture images of an eye of the wearer reflected from the mirrors. The HMD may also include a mirror angle adjustment device to adjust an angle of one or more of the mirrors relative to the imaging device so that the mirror(s) reflect the eye of the wearer to the imaging device.
G02B 27/00 - Systèmes ou appareils optiques non prévus dans aucun des groupes ,
G02B 27/09 - Mise en forme du faisceau, p.ex. changement de la section transversale, non prévue ailleurs
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
A hardware acceleration module may generate a channel-wise argmax map using a predefined set of hardware-implemented operations. In some examples, a hardware acceleration module may receive a set of feature maps for different image channels. The hardware acceleration module may execute a sequence of hardware operations, including a portion(s) of hardware for executing a convolution, rectified linear unit (ReLU) activation, and/or layer concatenation, to determine a maximum channel feature value and/or argument maxima (argmax) value for a set of associated locations within the feature maps. An argmax map may be generated based at least in part on the argument maximum for a set of associated locations.
G06F 30/331 - Vérification de la conception, p.ex. simulation fonctionnelle ou vérification du modèle par simulation avec accélération matérielle, p.ex. en utilisant les réseaux de portes programmables [FPGA] ou une émulation
G06T 7/33 - Détermination des paramètres de transformation pour l'alignement des images, c. à d. recalage des images utilisant des procédés basés sur les caractéristiques
G06F 7/483 - Calculs avec des nombres représentés par une combinaison non linéaire de nombres codés, p.ex. nombres rationnels, système de numération logarithmique ou nombres à virgule flottante
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
A method operable within an image capture device for stabilizing a sequence of images captured by the image capture device is disclosed. The method comprises, using lens based sensors indicating image capture device movement during image acquisition, performing optical image stabilization (OIS) during acquisition of each image of the sequence of images to provide a sequence of OIS corrected images. Movement of the device for each frame during which each OIS corrected image is captured is determined using inertial measurement sensors. At least an estimate of OIS control performed during acquisition of an image is obtained. The estimate is removed from the intra-frame movement determined for the frame during which the OIS corrected image was captured to provide a residual measurement of movement for the frame. Electronic image stabilization (EIS) of each OIS corrected image based on the residual measurement is performed to provide a stabilized sequence of images.
A camera comprises a lens assembly coupled to an event-sensor, the lens assembly being configured to focus a light field onto a surface of the event-sensor, the event-sensor surface comprising a plurality of light sensitive-pixels, each of which cause an event to be generated when there is a change in light intensity greater than a threshold amount incident on the pixel. The camera further includes an actuator which can be triggered to cause a change in the light field incident on the surface of the event-sensor and to generate a set of events from a sub-set of pixels distributed across the surface of the event-sensor.
G06K 9/60 - Combinaison de l'obtention de l'image et des fonctions de prétraitement
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
H04N 5/341 - Extraction de données de pixels provenant d'un capteur d'images en agissant sur les circuits de balayage, p.ex. en modifiant le nombre de pixels ayant été échantillonnés ou à échantillonner
28.
Systems and methods for synthesizing high resolution images using images captured by an array of independently controllable imagers
Systems and methods in accordance with embodiments of the invention are disclosed that use super-resolution (SR) processes to use information from a plurality of low resolution (LR) images captured by an array camera to produce a synthesized higher resolution image. One embodiment includes obtaining input images using the plurality of imagers, using a microprocessor to determine an initial estimate of at least a portion of a high resolution image using a plurality of pixels from the input images, and using a microprocessor to determine a high resolution image that when mapped through the forward imaging transformation matches the input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image. In addition, each forward imaging transformation corresponds to the manner in which each imager in the imaging array generate the input images, and the high resolution image synthesized by the microprocessor has a resolution that is greater than any of the input images.
A camera comprises a lens assembly coupled to an event-sensor, the lens assembly being configured to focus a light field onto a surface of the event-sensor, the event-sensor surface comprising a plurality of light sensitive-pixels, each of which cause an event to be generated when there is a change in light intensity greater than a threshold amount incident on the pixel. The camera further includes an actuator which can be triggered to cause a change in the light field incident on the surface of the event-sensor and to generate a set of events from a sub-set of pixels distributed across the surface of the event-sensor.
H04N 5/345 - Extraction de données de pixels provenant d'un capteur d'images en agissant sur les circuits de balayage, p.ex. en modifiant le nombre de pixels ayant été échantillonnés ou à échantillonner en lisant partiellement une matrice de capteurs SSIS
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
G02B 27/64 - Systèmes pour donner des images utilisant des éléments optiques pour la stabilisation latérale et angulaire de l'image
The technology relates to tuning a data translation block (DTB) including a generator model and a discriminator model. One or more processors may be configured to receive training data including an image in a second domain. The image in the second domain may be transformed into a first domain with a generator model. The transformed image may be processed to determine one or more outputs with one or more deep neural networks (DNNs) trained to process data in the first domain. An original objective function for the DTB may be updated based on the one or more outputs. The generator and discriminator models may be trained to satisfy the updated objective function.
Systems and methods for estimating depth from projected texture using camera arrays are described. A camera array includes a conventional camera and at least one two-dimensional array of cameras, where the conventional camera has a higher resolution than the cameras in the at least one two-dimensional array of cameras, an illumination system configured to illuminate a scene with a projected texture, where an image processing pipeline application directs the processor to: utilize the illumination system controller application to control the illumination system to illuminate a scene with a projected texture, capture a set of images of the scene illuminated with the projected texture, and determining depth estimates for pixel locations in an image from a reference viewpoint using at least a subset of the set of images.
G01B 11/22 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer la profondeur
G01B 11/25 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer des contours ou des courbes en projetant un motif, p.ex. des franges de moiré, sur l'objet
G06T 7/521 - Récupération de la profondeur ou de la forme à partir de la projection de lumière structurée
G06T 7/593 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir d’images stéréo
G06T 7/557 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir des champs de lumière, p.ex. de caméras plénoptiques
A method and system for detecting facial expressions in digital images and applications therefore are disclosed. Analysis of a digital image determines whether or not a smile and/or blink is present on a person's face. Face recognition, and/or a pose or illumination condition determination, permits application of a specific, relatively small classifier cascade.
A method of generating landmark locations for an image crop comprises: processing the crop through an encoder-decoder to provide a plurality of N output maps of comparable spatial resolution to the crop, each output map corresponding to a respective landmark of an object appearing in the image crop; processing an output map from the encoder through a plurality of feed forward layers to provide a feature vector comprising N elements, each element including an (x,y) location for a respective landmark. Any landmarks locations from the feature vector having an x or a y location outside a range for a respective row or column of the crop are selected for a final set of landmark locations; with remaining landmark locations tending to be selected from the N (x,y) landmark locations from the plurality of N output maps.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
Embodiments of the invention provide a camera array imaging architecture that computes depth maps for objects within a scene captured by the cameras, and use a near-field sub-array of cameras to compute depth to near-field objects and a far-field sub-array of cameras to compute depth to far-field objects. In particular, a baseline distance between cameras in the near-field subarray is less than a baseline distance between cameras in the far-field sub-array in order to increase the accuracy of the depth map. Some embodiments provide an illumination near-IR light source for use in computing depth maps.
A method for correcting an image divides an output image into a grid with vertical sections of width smaller than the image width but wide enough to allow efficient bursts when writing distortion corrected line sections into memory. A distortion correction engine includes a relatively small amount of memory for an input image buffer but without requiring unduly complex control. The input image buffer accommodates enough lines of an input image to cover the distortion of a single most vertically distorted line section of the input image. The memory required for the input image buffer can be significantly less than would be required to store all the lines of a distorted input image spanning a maximal distortion of a complete line within the input image.
A method for automatically determining exposure settings for an image acquisition system comprises maintaining a plurality of look-up tables, each look-up table being associated with a corresponding light condition and storing image exposure settings associated with corresponding distance values between a subject and the image acquisition system. An image of a subject is acquired from a camera module; and a light condition occurring during the acquisition is determined based on the acquired image. A distance between the subject and the camera module during the acquisition is calculated. The method then determines whether a correction of the image exposure settings for the camera module is required based on the calculated distance and the determined light condition; and responsive to correction being required: selects image exposure settings corresponding to the calculated distance from the look-up table corresponding to the determined light condition; and acquires a new image using the selected image exposure settings.
G06V 40/00 - Reconnaissance de formes biométriques, liées aux êtres humains ou aux animaux, dans les données d’image ou vidéo
H04N 5/235 - Circuits pour la compensation des variations de la luminance de l'objet
G01S 3/00 - Radiogoniomètres pour déterminer la direction d'où proviennent des ondes infrasonores, sonores, ultrasonores ou électromagnétiques ou des émissions de particules sans caractéristiques de direction
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
H04N 5/243 - Circuits pour la compensation des variations de la luminance de l'objet en agissant sur le signal d'image
G08B 13/196 - Déclenchement influencé par la chaleur, la lumière, ou les radiations de longueur d'onde plus courte; Déclenchement par introduction de sources de chaleur, de lumière, ou de radiations de longueur d'onde plus courte utilisant des systèmes détecteurs de radiations passifs utilisant des systèmes de balayage et de comparaison d'image utilisant des caméras de télévision
37.
Capturing and processing of images including occlusions focused on an image sensor by a lens stack array
Systems and methods for implementing array cameras configured to perform super-resolution processing to generate higher resolution super-resolved images using a plurality of captured images and lens stack arrays that can be utilized in array cameras are disclosed. An imaging device in accordance with one embodiment of the invention includes at least one imager array, and each imager in the array comprises a plurality of light sensing elements and a lens stack including at least one lens surface, where the lens stack is configured to form an image on the light sensing elements, control circuitry configured to capture images formed on the light sensing elements of each of the imagers, and a super-resolution processing module configured to generate at least one higher resolution super-resolved image using a plurality of the captured images.
H04N 5/365 - Traitement du bruit, p.ex. détection, correction, réduction ou élimination du bruit appliqué au bruit à motif fixe, p.ex. non-uniformité de la réponse
H04N 13/128 - Ajustement de la profondeur ou de la disparité
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
H04N 5/33 - Transformation des rayonnements infrarouges
H04N 5/341 - Extraction de données de pixels provenant d'un capteur d'images en agissant sur les circuits de balayage, p.ex. en modifiant le nombre de pixels ayant été échantillonnés ou à échantillonner
H04N 5/349 - Extraction de données de pixels provenant d'un capteur d'images en agissant sur les circuits de balayage, p.ex. en modifiant le nombre de pixels ayant été échantillonnés ou à échantillonner pour accroître la résolution en déplaçant le capteur par rapport à la scène
H04N 5/357 - Traitement du bruit, p.ex. détection, correction, réduction ou élimination du bruit
G06T 7/557 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir des champs de lumière, p.ex. de caméras plénoptiques
H04N 13/239 - Générateurs de signaux d’images utilisant des caméras à images stéréoscopiques utilisant deux capteurs d’images 2D dont la position relative est égale ou en correspondance à l’intervalle oculaire
G06T 7/50 - Récupération de la profondeur ou de la forme
H04N 9/097 - Dispositions optiques associées aux dispositifs analyseurs, p.ex. pour partager des faisceaux, pour corriger la couleur
G06T 19/20 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie Édition d'images tridimensionnelles [3D], p.ex. modification de formes ou de couleurs, alignement d'objets ou positionnements de parties
H04N 9/09 - Générateurs de signaux d'image avec plusieurs têtes de lecture
H04N 9/73 - Circuits pour l'équilibrage des couleurs, p.ex. circuits pour équilibrer le blanc ou commande de la température de couleur
This disclosure describes, in part, devices and techniques for performing biometric identification for an electronic device. For instance, the electronic device may include one or more near-infrared illuminators that output near-infrared light. The one or more near-infrared illuminators may be located in or on a bezel and/or a display of the electronic device. The electronic device may also include an imaging device that generates first image data representing the near-infrared light and visible light. After generating the image data, the electronic device may process the first image data using one or more image processing techniques to generate second image data representing a near-infrared image and third image data representing a visible image. The electronic device may then analyze the second image data and/or the third image data using one or more biometric identification techniques. Based on the analysis, the electronic device may identify a person possessing the electronic device.
A multi-camera vision system and method of monitoring. In one embodiment imaging systems provide object classifications with cameras positioned to receive image data from a field of view to classify an object among multiple classifications. A control unit receives classification or position information of objects and (ii) displays an image corresponding to a classified object relative to the position of the structure. An embodiment of a related method monitors positions of an imaged object about a boundary by continually capturing at least first and second series of image frames, each series comprising different fields of view of a scene about the boundary, with some of the image frames in the first series covering a wide angle field of view and some of the image frames in the second series covering no more than a narrow angle field of view.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
H04N 7/18 - Systèmes de télévision en circuit fermé [CCTV], c. à d. systèmes dans lesquels le signal vidéo n'est pas diffusé
In an embodiment, a 3D facial modeling system includes a plurality of cameras configured to capture images from different viewpoints, a processor, and a memory containing a 3D facial modeling application and parameters defining a face detector, wherein the 3D facial modeling application directs the processor to obtain a plurality of images of a face captured from different viewpoints using the plurality of cameras, locate a face within each of the plurality of images using the face detector, wherein the face detector labels key feature points on the located face within each of the plurality of images, determine disparity between corresponding key feature points of located faces within the plurality of images, and generate a 3D model of the face using the depth of the key feature points.
G06T 17/20 - Description filaire, p.ex. polygonalisation ou tessellation
G06T 7/149 - Découpage; Détection de bords impliquant des modèles déformables, p.ex. des modèles de contours actifs
G06T 7/593 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir d’images stéréo
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
41.
System for performing eye detection and/or tracking
This disclosure describes, in part, systems and techniques for performing eye tracking. For instance, a system may include a first imaging device that generates first image data. The system may then analyze the first image data to determine a location of a face of a user. Using the location, the system may cause an actuator to move from a first position to a second position in order to direct a second imaging device towards the face of the user. While in the second position, the second imaging device may generate second image data representing at least the face of the user. The system may then analyze the second image data to determine a gaze direction of the user. In some instances, the first imaging device may include a first field of view (FOV) that is greater than a second FOV of the second imaging device.
G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
B60Q 3/18 - Circuits; Agencements de commande pour faire varier l’intensité de la lumière
B60R 11/04 - Montage des caméras pour fonctionner pendant la marche; Disposition de leur commande par rapport au véhicule
G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
B60R 11/00 - Autres aménagements pour tenir ou monter des objets
B60W 40/08 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conducteurs ou aux passagers
42.
System for performing eye detection and/or tracking
This disclosure describes, in part, systems and techniques for performing eye tracking. For instance, a system may include a first imaging device that generates first image data. The system may then analyze the first image data to determine a location of a face of a user. Using the location, the system may cause an actuator to move from a first position to a second position in order to direct a second imaging device towards the face of the user. While in the second position, the second imaging device may generate second image data representing at least the face of the user. The system may then analyze the second image data to determine a gaze direction of the user. In some instances, the first imaging device may include a first field of view (FOV) that is greater than a second FOV of the second imaging device.
G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
H04N 5/247 - Disposition des caméras de télévision
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
43.
Method of providing a sharpness measure for an image
A method of providing a sharpness measure for an image comprises detecting an object region within an image; obtaining meta-data for the image; and scaling the chosen object region to a fixed size. A gradient map is calculated for the scaled object region and compared against a threshold determined for the image to provide a filtered gradient map of values exceeding the threshold. The threshold for the image is a function of at least: a contrast level for the detected object region, a distance to the subject and an ISO/gain used for image acquisition. A sharpness measure for the object region is determined as a function of the filtered gradient map values, the sharpness measure being proportional to the filtered gradient map values.
G06T 7/42 - Analyse de la texture basée sur la description statistique de texture utilisant des procédés de transformation de domaine
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
A biometrics-enabled portable storage device may store and secure data via biometrics related to a user's iris. The biometrics-enabled portable storage device may include a camera that captures image data related a user's iris and stores the image data to enroll the user for use of the biometrics-enabled portable storage device. To unlock the data, a user aligns the camera with their iris using a hot mirror and the camera captures iris data for comparison with the iris image data stored during enrollment. If the two sets of image data match, the biometrics-enabled portable storage device may be unlocked and the user may access data stored on the biometrics-enabled portable storage device. If the two sets of image data do not match, then the biometrics-enabled portable storage device remains locked.
A neural network engine comprises a plurality of floating point multipliers, each having an input connected to an input map value and an input connected to a corresponding kernel value. Pairs of multipliers provide outputs to a tree of nodes, each node of the tree being configured to provide a floating point output corresponding to either: a larger of the inputs of the node; or a sum of the inputs, one output node of the tree providing a first input of an output module, and one of the multipliers providing an output to a second input of the output module. The engine is configured to process either a convolution layer of a neural network, an average pooling layer or a max pooling layer according to the kernel values and whether the nodes and output module are configured to output a larger or a sum of their inputs.
Systems and methods for calibrating an array camera are disclosed. Systems and methods for calibrating an array camera in accordance with embodiments of this invention include the capturing of an image of a test pattern with the array camera such that each imaging component in the array camera captures an image of the test pattern. The image of the test pattern captured by a reference imaging component is then used to derive calibration information for the reference component. A corrected image of the test pattern for the reference component is then generated from the calibration information and the image of the test pattern captured by the reference imaging component. The corrected image is then used with the images captured by each of the associate imaging components associated with the reference component to generate calibration information for the associate imaging components.
H04N 13/282 - Générateurs de signaux d’images pour la génération de signaux d’images correspondant à au moins trois points de vue géométriques, p.ex. systèmes multi-vues
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
G06T 7/80 - Analyse des images capturées pour déterminer les paramètres de caméra intrinsèques ou extrinsèques, c. à d. étalonnage de caméra
H04N 17/02 - Diagnostic, test ou mesure, ou leurs détails, pour les systèmes de télévision pour les signaux de télévision en couleurs
G02B 7/02 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour lentilles
G02B 9/64 - Objectifs optiques caractérisés à la fois par le nombre de leurs composants et la façon dont ceux-ci sont disposés selon leur signe, c. à d. + ou — ayant plus de six composants
48.
Systems and methods for hybrid depth regularization
Systems and methods for hybrid depth regularization in accordance with various embodiments of the invention are disclosed. In one embodiment of the invention, a depth sensing system comprises a plurality of cameras; a processor; and a memory containing an image processing application. The image processing application may direct the processor to obtain image data for a plurality of images from multiple viewpoints, the image data comprising a reference image and at least one alternate view image; generate a raw depth map using a first depth estimation process, and a confidence map; and generate a regularized depth map. The regularized depth map may be generated by computing a secondary depth map using a second different depth estimation process; and computing a composite depth map by selecting depth estimates from the raw depth map and the secondary depth map based on the confidence map.
G06T 7/593 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir d’images stéréo
G06T 7/44 - Analyse de la texture basée sur la description statistique de texture utilisant des opérateurs de l'image, p.ex. des filtres, des mesures de densité des bords ou des histogrammes locaux
The present invention relates to an image processing apparatus which determines an order for calculating output image pixels that maximally reuses data in a local memory for computing all relevant output image pixels. Thus, the same set of data is re-used until it is no longer necessary. Output image pixel locations are browsed to determine pixel values in an order imposed by available input data, rather than in an order imposed by pixel positions in the output image. Consequently, the amount of storage required for local memory as well as the number of input image read requests and data read from memory containing the input image is minimized.
A convolutional neural network (CNN) for an image processing system comprises an image cache responsive to a request to read a block of N×M pixels extending from a specified location within an input map to provide a block of N×M pixels at an output port. A convolution engine reads blocks of pixels from the output port, combines blocks of pixels with a corresponding set of weights to provide a product, and subjects the product to an activation function to provide an output pixel value. The image cache comprises a plurality of interleaved memories capable of simultaneously providing the N×M pixels at the output port in a single clock cycle. A controller provides a set of weights to the convolution engine before processing an input map, causes the convolution engine to scan across the input map by incrementing a specified location for successive blocks of pixels and generates an output map within the image cache by writing output pixel values to successive locations within the image cache.
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
A system includes an image sensor, an adjustable aperture, and a memory. THE memory includes computer executable instructions that, when executed by a processor, cause the system to perform operations including obtaining a first image via the image sensor based at least in part on a first aperture stop of the adjustable aperture, identifying a first pixel of the first image, identifying a second pixel of the first image, determining a second aperture stop of the adjustable aperture based at least in part on the first pixel, determining a third aperture stop of the adjustable aperture based at least in part on the second pixel, obtaining a second image via the image sensor based at least in part on the second aperture stop, and obtaining a third image via the image sensor based at least in part on the third aperture stop.
An image processing method for iris recognition of a predetermined subject, comprises acquiring through an image sensor, a probe image illuminated by an infra-red (IR) illumination source, wherein the probe image comprises one or more eye regions and is overexposed until skin portions of the image are saturated. One or more iris regions are identified within the one or more eye regions of said probe image; and the identified iris regions are analysed to detect whether they belong to the predetermined subject.
H04N 5/33 - Transformation des rayonnements infrarouges
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06T 7/33 - Détermination des paramètres de transformation pour l'alignement des images, c. à d. recalage des images utilisant des procédés basés sur les caractéristiques
54.
Systems and methods for encoding image files containing depth maps stored as metadata
Systems and methods in accordance with embodiments of the invention are configured to render images using light field image files containing an image synthesized from light field image data and metadata describing the image that includes a depth map. One embodiment of the invention includes a processor and memory containing a rendering application and a light field image file including an encoded image, a set of low resolution images, and metadata describing the encoded image, where the metadata comprises a depth map that specifies depths from the reference viewpoint for pixels in the encoded image. In addition, the rendering application configures the processor to: locate the encoded image within the light field image file; decode the encoded image; locate the metadata within the light field image file; and post process the decoded image by modifying the pixels based on the depths indicated within the depth map and the set of low resolution images to create a rendered image.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06K 9/36 - Prétraitement de l'image, c. à d. traitement de l'information image sans se préoccuper de l'identité de l'image
H04N 13/128 - Ajustement de la profondeur ou de la disparité
H04N 13/161 - Encodage, multiplexage ou démultiplexage de différentes composantes des signaux d’images
H04N 13/243 - Générateurs de signaux d’images utilisant des caméras à images stéréoscopiques utilisant au moins trois capteurs d’images 2D
H04N 13/271 - Générateurs de signaux d’images où les signaux d’images générés comprennent des cartes de profondeur ou de disparité
G06T 7/50 - Récupération de la profondeur ou de la forme
G06T 9/20 - Codage des contours, p.ex. utilisant la détection des contours
H04N 19/597 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage prédictif spécialement adapté pour l’encodage de séquences vidéo multi-vues
H04N 19/625 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant un codage par transformée utilisant une transformée en cosinus discrète
H04N 19/136 - Caractéristiques ou propriétés du signal vidéo entrant
G06T 3/40 - Changement d'échelle d'une image entière ou d'une partie d'image
H04N 19/85 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le pré-traitement ou le post-traitement spécialement adaptés pour la compression vidéo
A method is disclosed for processing at least a portion of an input digital image comprising rows of pixels extending in two mutually perpendicular directions over a 2D field. The method comprises defining a kernel for processing an image, the kernel comprising at least one row of contiguous elements of the same non-zero value (such rows being referred to herein as equal-valued kernel regions), the equal-valued kernel regions, if more than one, extending parallel to one another. For each pixel in at least selected parallel rows of pixels within the image portion, the cumulative sum of the pixel is calculated by adding a value of the pixel to the sum of all preceding pixel values in the same row of the image portion. The kernel is convolved with the image portion at successive kernel positions relative to the image portion such that each pixel in each selected row is a target pixel for a respective kernel position. For each kernel position, the convolving is performed, for each equal-valued kernel region, by calculating the difference between the cumulative sum of the pixel corresponding to the last element in the equal-valued kernel region and the cumulative sum of the pixel corresponding to the element immediately preceding the first element in the region, and summing the differences for all equal-valued kernel regions. The differences sum is scaled to provide a processed target pixel value.
A dynamically reconfigurable heterogeneous systolic array is configured to process a first image frame, and to generate image processing primitives from the image frame, and to store the primitives and the corresponding image frame in a memory store. A characteristic of the image frame is determined. Based on the characteristic, the array is reconfigured to process a following image frame.
G09G 5/393 - Dispositions pour la mise à jour du contenu de la mémoire à mappage binaire
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
H04N 9/67 - Circuits pour le traitement de signaux de couleur pour le matriçage
H04N 5/335 - Transformation d'informations lumineuses ou analogues en informations électriques utilisant des capteurs d'images à l'état solide [capteurs SSIS]
G06F 15/80 - Architectures de calculateurs universels à programmes enregistrés comprenant un ensemble d'unités de traitement à commande commune, p.ex. plusieurs processeurs de données à instruction unique
57.
Multispectral image processing system for face detection
An image processing system comprises at least one image sensor comprising a plurality of sub-pixels, and configured to provide a first image plane from a group of first sub-pixels selectively sensitive to a first NIR light band and a second image plane from a group of second sub-pixels selectively sensitive to a second NIR light band. An NIR light source is capable of separately emitting first NIR light corresponding to the first NIR light band and second NIR light corresponding to the second NIR light band. The system can be configured to operate according to at least a first working mode where a face detector is configured to detect at least a first face in the first image plane and a second face in the second image plane at a spatially non-coincident location to the first face.
H04N 5/33 - Transformation des rayonnements infrarouges
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
Systems in accordance with embodiments of the invention can perform parallax detection and correction in images captured using array cameras. Due to the different viewpoints of the cameras, parallax results in variations in the position of objects within the captured images of the scene. Methods in accordance with embodiments of the invention provide an accurate account of the pixel disparity due to parallax between the different cameras in the array, so that appropriate scene-dependent geometric shifts can be applied to the pixels of the captured images when performing super-resolution processing. In a number of embodiments, generating depth estimates considers the similarity of pixels in multiple spectral channels. In certain embodiments, generating depth estimates involves generating a confidence map indicating the reliability of depth estimates.
H04N 13/232 - Générateurs de signaux d’images utilisant des caméras à images stéréoscopiques utilisant un seul capteur d’images 2D utilisant des lentilles du type œil de mouche, p.ex. dispositions de lentilles circulaires
H04N 9/097 - Dispositions optiques associées aux dispositifs analyseurs, p.ex. pour partager des faisceaux, pour corriger la couleur
Systems and methods for implementing array cameras configured to perform super-resolution processing to generate higher resolution super-resolved images using a plurality of captured images and lens stack arrays that can be utilized in array cameras are disclosed. An imaging device in accordance with one embodiment of the invention includes at least one imager array, and each imager in the array comprises a plurality of light sensing elements and a lens stack including at least one lens surface, where the lens stack is configured to form an image on the light sensing elements, control circuitry configured to capture images formed on the light sensing elements of each of the imagers, and a super-resolution processing module configured to generate at least one higher resolution super-resolved image using a plurality of the captured images.
H04N 13/239 - Générateurs de signaux d’images utilisant des caméras à images stéréoscopiques utilisant deux capteurs d’images 2D dont la position relative est égale ou en correspondance à l’intervalle oculaire
H04N 5/247 - Disposition des caméras de télévision
G02B 13/00 - Objectifs optiques spécialement conçus pour les emplois spécifiés ci-dessous
H04N 5/365 - Traitement du bruit, p.ex. détection, correction, réduction ou élimination du bruit appliqué au bruit à motif fixe, p.ex. non-uniformité de la réponse
H04N 13/128 - Ajustement de la profondeur ou de la disparité
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
H04N 5/33 - Transformation des rayonnements infrarouges
H04N 5/341 - Extraction de données de pixels provenant d'un capteur d'images en agissant sur les circuits de balayage, p.ex. en modifiant le nombre de pixels ayant été échantillonnés ou à échantillonner
H04N 5/349 - Extraction de données de pixels provenant d'un capteur d'images en agissant sur les circuits de balayage, p.ex. en modifiant le nombre de pixels ayant été échantillonnés ou à échantillonner pour accroître la résolution en déplaçant le capteur par rapport à la scène
G06T 7/557 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir des champs de lumière, p.ex. de caméras plénoptiques
G06T 7/50 - Récupération de la profondeur ou de la forme
H04N 9/097 - Dispositions optiques associées aux dispositifs analyseurs, p.ex. pour partager des faisceaux, pour corriger la couleur
G06T 19/20 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie Édition d'images tridimensionnelles [3D], p.ex. modification de formes ou de couleurs, alignement d'objets ou positionnements de parties
H04N 9/09 - Générateurs de signaux d'image avec plusieurs têtes de lecture
H04N 9/73 - Circuits pour l'équilibrage des couleurs, p.ex. circuits pour équilibrer le blanc ou commande de la température de couleur
H04N 5/262 - Circuits de studio, p.ex. pour mélanger, commuter, changer le caractère de l'image, pour d'autres effets spéciaux
Systems and methods in accordance with embodiments of the invention are disclosed that use super-resolution (SR) processes to use information from a plurality of low resolution (LR) images captured by an array camera to produce a synthesized higher resolution image. One embodiment includes obtaining input images using the plurality of imagers, using a microprocessor to determine an initial estimate of at least a portion of a high resolution image using a plurality of pixels from the input images, and using a microprocessor to determine a high resolution image that when mapped through the forward imaging transformation matches the input images to within at least one predetermined criterion using the initial estimate of at least a portion of the high resolution image. In addition, each forward imaging transformation corresponds to the manner in which each imager in the imaging array generate the input images, and the high resolution image synthesized by the microprocessor has a resolution that is greater than any of the input images.
A method for providing depth map information based on image data descriptive of a scene. In one embodiment, after generating an initial sequence of disparity map data, performing a smoothing operation or an interpolation to remove artifact introduced in the disparity map data as a result of segmenting the image data into superpixels.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06T 7/50 - Récupération de la profondeur ou de la forme
A method for compensating for off-axis tilting of a lens relative to an image sensor in an image acquisition device comprises acquiring a set of calibrated parameters
y indicate a coordinate of a pixel in an acquired image. Image information is mapped from the acquired image to a lens tilt compensated image according to the formulae:
where s comprises a scale factor given by
y indicate the location of a pixel in the lens tilt compensated image.
A neural network engine comprises a plurality of floating point multipliers, each having an input connected to an input map value and an input connected to a corresponding kernel value. Pairs of multipliers provide outputs to a tree of nodes, each node of the tree being configured to provide a floating point output corresponding to either: a larger of the inputs of the node; or a sum of the inputs, one output node of the tree providing a first input of an output module, and one of the multipliers providing an output to a second input of the output module. The engine is configured to process either a convolution layer of a neural network, an average pooling layer or a max pooling layer according to the kernel values and whether the nodes and output module are configured to output a larger or a sum of their inputs.
Systems and methods for implementing array cameras configured to perform super-resolution processing to generate higher resolution super-resolved images using a plurality of captured images and lens stack arrays that can be utilized in array cameras are disclosed. Lens stack arrays in accordance with many embodiments of the invention include lens elements formed on substrates separated by spacers, where the lens elements, substrates and spacers are configured to form a plurality of optical channels, at least one aperture located within each optical channel, at least one spectral filter located within each optical channel, where each spectral filter is configured to pass a specific spectral band of light, and light blocking materials located within the lens stack array to optically isolate the optical channels.
H04N 5/341 - Extraction de données de pixels provenant d'un capteur d'images en agissant sur les circuits de balayage, p.ex. en modifiant le nombre de pixels ayant été échantillonnés ou à échantillonner
A method of providing a sharpness measure for an image comprises detecting an object region within an image; obtaining meta-data for the image; and scaling the chosen object region to a fixed size. A gradient map is calculated for the scaled object region and compared against a threshold determined for the image to provide a filtered gradient map of values exceeding the threshold. The threshold for the image is a function of at least: a contrast level for the detected object region, a distance to the subject and an ISO/gain used for image acquisition. A sharpness measure for the object region is determined as a function of the filtered gradient map values, the sharpness measure being proportional to the filtered gradient map values.
G06T 7/42 - Analyse de la texture basée sur la description statistique de texture utilisant des procédés de transformation de domaine
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
A method of estimating motion between a pair of image frames of a given scene comprises calculating respective integral images for each of the image frames and selecting at least one corresponding region of interest within each frame. For each region of interest, an integral image profile from each integral image is calculated, each profile comprising an array of elements, each element comprising a sum of pixel intensities from successive swaths of the region of interest for the frame. Integral image profiles are correlated to determine a relative displacement of the region of interest between the pair of frames. Each region of interest is divided into a plurality of further regions of interest before repeating until a required hierarchy of estimated motion for successively divided regions of interest is provided.
An image processing apparatus comprises a set of infra-red (IR) sources surrounding an image capture sensor and a processor operatively coupled to said IR sources and said image capture sensor. The processor being arranged to acquire from the sensor a succession of images, each illuminated with a different combination of the IR sources. The processor is further arranged to combine component images corresponding to the succession of images by selecting a median value for corresponding pixel locations of the component images as a pixel value for the combined image.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
Systems and methods for calibrating an array camera are disclosed. Systems and methods for calibrating an array camera in accordance with embodiments of this invention include the capturing of an image of a test pattern with the array camera such that each imaging component in the array camera captures an image of the test pattern. The image of the test pattern captured by a reference imaging component is then used to derive calibration information for the reference component. A corrected image of the test pattern for the reference component is then generated from the calibration information and the image of the test pattern captured by the reference imaging component. The corrected image is then used with the images captured by each of the associate imaging components associated with the reference component to generate calibration information for the associate imaging components.
H04N 13/282 - Générateurs de signaux d’images pour la génération de signaux d’images correspondant à au moins trois points de vue géométriques, p.ex. systèmes multi-vues
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
G06T 7/80 - Analyse des images capturées pour déterminer les paramètres de caméra intrinsèques ou extrinsèques, c. à d. étalonnage de caméra
H04N 17/02 - Diagnostic, test ou mesure, ou leurs détails, pour les systèmes de télévision pour les signaux de télévision en couleurs
An iris image acquisition system for a mobile device, comprises a lens assembly arranged along an optical axis and configured for forming an image comprising at least one iris of a subject disposed frontally to the lens assembly; and an image sensor configured to acquire the formed image. The lens assembly comprises a first lens refractive element and at least one second lens element for converging incident radiation to the first refractive element. The first refractive element has a variable thickness configured to counteract a shift of the formed image along the optical axis induced by change in iris-lens assembly distance, such that different areas of the image sensor on which irises at different respective iris-lens assembly distances are formed are in focus within a range of respective iris-lens assembly distances at which iris detail is provided at sufficient contrast to be recognised.
G02B 13/18 - Objectifs optiques spécialement conçus pour les emplois spécifiés ci-dessous avec des lentilles ayant une ou plusieurs surfaces non sphériques, p.ex. pour réduire l'aberration géométrique
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G02B 5/00 - OPTIQUE ÉLÉMENTS, SYSTÈMES OU APPAREILS OPTIQUES Éléments optiques autres que les lentilles
70.
Systems and methods for depth estimation using generative models
Systems and methods for depth estimation in accordance with embodiments of the invention are illustrated. One embodiment includes a method for estimating depth from images. The method includes steps for receiving a plurality of source images captured from a plurality of different viewpoints using a processing system configured by an image processing application, generating a target image from a target viewpoint that is different to the viewpoints of the plurality of source images based upon a set of generative model parameters using the processing system configured by the image processing application, and identifying depth information of at least one output image based on the predicted target image using the processing system configured by the image processing application.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06T 7/55 - Récupération de la profondeur ou de la forme à partir de plusieurs images
G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
Systems and methods in accordance with embodiments of the invention implement optical systems incorporating lens elements formed separately and subsequently bonded to low coefficient of thermal expansion substrates. Optical systems in accordance with various embodiments of the invention can be utilized in single aperture cameras, and multiple-aperture array cameras. In one embodiment, a robust optical system includes at least one carrier characterized by a low coefficient of thermal expansion to which at least a primary lens element formed from precision molded glass is bonded.
G02B 7/02 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour lentilles
B29D 11/00 - Fabrication d'éléments optiques, p.ex. lentilles ou prismes
G02B 1/04 - OPTIQUE ÉLÉMENTS, SYSTÈMES OU APPAREILS OPTIQUES Éléments optiques caractérisés par la substance dont ils sont faits; Revêtements optiques pour éléments optiques faits de substances organiques, p.ex. plastiques
G03B 17/12 - Corps d'appareils avec moyens pour supporter des objectifs, des lentilles additionnelles, des filtres, des masques ou des tourelles
H04N 9/07 - Générateurs de signaux d'image avec une seule tête de lecture
A method of iris recognition comprises detecting a body region larger than and comprising at least one iris in an image and performing a first eye modelling on the detected body region. If successful, the result of first iris segmentation based on the first eye model is chosen. Otherwise, a first iris identification is performed on the detected body region. If successful, the result of second iris segmentation based on a second eye modelling is chosen. Otherwise, second iris identification is performed on the image, third eye modelling is performed on the result of the second iris identification, and third iris segmentation is performed on the result of the third eye modelling. If successful, the result of third iris segmentation based on a third eye modelling is chosen. An iris code is extracted from any selected iris segment of the image.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
Systems and methods in accordance with embodiments of the invention actively align a lens stack array with an array of focal planes to construct an array camera module. In one embodiment, a method for actively aligning a lens stack array with a sensor that has a focal plane array includes: aligning the lens stack array relative to the sensor in an initial position; varying the spatial relationship between the lens stack array and the sensor; capturing images of a known target that has a region of interest using a plurality of active focal planes at different spatial relationships; scoring the images based on the extent to which the region of interest is focused in the images; selecting a spatial relationship between the lens stack array and the sensor based on a comparison of the scores; and forming an array camera subassembly based on the selected spatial relationship.
H04N 17/00 - Diagnostic, test ou mesure, ou leurs détails, pour les systèmes de télévision
G02B 7/00 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques
H04N 5/341 - Extraction de données de pixels provenant d'un capteur d'images en agissant sur les circuits de balayage, p.ex. en modifiant le nombre de pixels ayant été échantillonnés ou à échantillonner
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
A neural network image processing apparatus arranged to acquire images from an image sensor and to: identify a ROI containing a face region in an image; determine at plurality of facial landmarks in the face region; use the facial landmarks to transform the face region within the ROI into a face region having a given pose; and use transformed landmarks within the transformed face region to identify a pair of eye regions within the transformed face region. Each identified eye region is fed to a respective first and second convolutional neural network, each network configured to produce a respective feature vector. Each feature vector is fed to respective eyelid opening level neural networks to obtain respective measures of eyelid opening for each eye region. The feature vectors are combined and to a gaze angle neural network to generate gaze yaw and pitch values substantially simultaneously with the eyelid opening values.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
75.
Systems and methods for dynamic calibration of array cameras
Systems and methods for dynamically calibrating an array camera to accommodate variations in geometry that can occur throughout its operational life are disclosed. The dynamic calibration processes can include acquiring a set of images of a scene and identifying corresponding features within the images. Geometric calibration data can be used to rectify the images and determine residual vectors for the geometric calibration data at locations where corresponding features are observed. The residual vectors can then be used to determine updated geometric calibration data for the camera array. In several embodiments, the residual vectors are used to generate a residual vector calibration data field that updates the geometric calibration data. In many embodiments, the residual vectors are used to select a set of geometric calibration from amongst a number of different sets of geometric calibration data that is the best fit for the current geometry of the camera array.
A method for correcting an image divides an output image into a grid with vertical sections of width smaller than the image width but wide enough to allow efficient bursts when writing distortion corrected line sections into memory. A distortion correction engine includes a relatively small amount of memory for an input image buffer but without requiring unduly complex control. The input image buffer accommodates enough lines of an input image to cover the distortion of a single most vertically distorted line section of the input image. The memory required for the input image buffer can be significantly less than would be required to store all the lines of a distorted input image spanning a maximal distortion of a complete line within the input image.
A method for compensating for off-axis tilting of a lens relative to an image sensor in an image acquisition device comprises acquiring a set of calibrated parameters
y′ indicate a coordinate of a pixel in an acquired image. Image information is mapped from the acquired image to a lens tilt compensated image according to the formulae:
where s comprises a scale factor given by
y indicate the location of a pixel in the lens tilt compensated image.
Systems and methods for extended color processing on Pelican array cameras in accordance with embodiments of the invention are disclosed. In one embodiment, a method of generating a high resolution image includes obtaining input images, where a first set of images includes information in a first band of visible wavelengths and a second set of images includes information in a second band of visible wavelengths and non-visible wavelengths, determining an initial estimate by combining the first set of images into a first fused image, combining the second set of images into a second fused image, spatially registering the fused images, denoising the fused images using bilateral filters, normalizing the second fused image in the photometric reference space of the first fused image, combining the fused images, determining a high resolution image that when mapped through a forward imaging transformation matches the input images within at least one predetermined criterion.
A hand-held or otherwise portable or spatial or temporal performance-based image capture device includes one or more lenses, an aperture and a main sensor for capturing an original main image. A secondary sensor and optical system are for capturing a reference image that has temporal and spatial overlap with the original image. The device performs an image processing method including capturing the main image with the main sensor and the reference image with the secondary sensor, and utilizing information from the reference image to enhance the main image. The main and secondary sensors are contained together within a housing.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06K 9/32 - Alignement ou centrage du capteur d'image ou de la zone image
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
H04N 5/235 - Circuits pour la compensation des variations de la luminance de l'objet
H04N 5/345 - Extraction de données de pixels provenant d'un capteur d'images en agissant sur les circuits de balayage, p.ex. en modifiant le nombre de pixels ayant été échantillonnés ou à échantillonner en lisant partiellement une matrice de capteurs SSIS
H04N 5/347 - Extraction de données de pixels provenant d'un capteur d'images en agissant sur les circuits de balayage, p.ex. en modifiant le nombre de pixels ayant été échantillonnés ou à échantillonner en combinant ou en mélangeant les pixels dans le capteur SSIS
H04N 5/77 - Circuits d'interface entre un appareil d'enregistrement et un autre appareil entre un appareil d'enregistrement et une caméra de télévision
H04N 9/804 - Transformation du signal de télévision pour l'enregistrement, p.ex. modulation, changement de fréquence; Transformation inverse pour la reproduction comportant une modulation par impulsions codées pour les composantes du signal d'image en couleurs
A method for producing a histogram of oriented gradients (HOG) for at least a portion of an image comprises dividing the image portion into cells, each cell comprising a plurality of image pixels. Then, for each image pixel of a cell, obtaining a horizontal gradient component, gx, and a vertical gradient component, gy, based on differences in pixel values along at least a row of the image and a column of the image respectively including the pixel; and allocating a gradient to one of a plurality of sectors, where n is a sector index, each sector extending through a range of orientation angles and at least some of the sectors being divided from adjacent sectors according to the inequalities: b*16
G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06K 9/48 - Extraction d'éléments ou de caractéristiques de l'image en codant le contour de la forme
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
G06T 1/20 - Architectures de processeurs; Configuration de processeurs p.ex. configuration en pipeline
81.
Systems and methods for transmitting and receiving array camera image data
Systems and methods for transmitting and receiving image data captured by an imager array including a plurality of focal planes are described. One embodiment of the invention includes capturing image data using a plurality of active focal planes in a camera module, where an image is formed on each active focal plane by a separate lens stack, generating lines of image data by interleaving the image data captured by the plurality of active focal planes, and transmitting the lines of image data and the additional data.
In an embodiment, a 3D facial modeling system includes a plurality of cameras configured to capture images from different viewpoints, a processor, and a memory containing a 3D facial modeling application and parameters defining a face detector, wherein the 3D facial modeling application directs the processor to obtain a plurality of images of a face captured from different viewpoints using the plurality of cameras, locate a face within each of the plurality of images using the face detector, wherein the face detector labels key feature points on the located face within each of the plurality of images, determine disparity between corresponding key feature points of located faces within the plurality of images, and generate a 3D model of the face using the depth of the key feature points.
In an embodiment, a 3D facial modeling system includes a plurality of cameras configured to capture images from different viewpoints, a processor, and a memory containing a 3D facial modeling application and parameters defining a face detector, wherein the 3D facial modeling application directs the processor to obtain a plurality of images of a face captured from different viewpoints using the plurality of cameras, locate a face within each of the plurality of images using the face detector, wherein the face detector labels key feature points on the located face within each of the plurality of images, determine disparity between corresponding key feature points of located faces within the plurality of images, and generate a 3D model of the face using the depth of the key feature points.
G06T 17/20 - Description filaire, p.ex. polygonalisation ou tessellation
G06T 7/149 - Découpage; Détection de bords impliquant des modèles déformables, p.ex. des modèles de contours actifs
G06T 7/593 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir d’images stéréo
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
84.
Method for dynamically calibrating an image capture device
INIT) for each of the first and second determined distances; and the stored calibrated lens actuator settings are adjusted according to the determined calibration corrections.
H04N 17/00 - Diagnostic, test ou mesure, ou leurs détails, pour les systèmes de télévision
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
G06T 7/80 - Analyse des images capturées pour déterminer les paramètres de caméra intrinsèques ou extrinsèques, c. à d. étalonnage de caméra
G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
G03B 13/36 - Systèmes de mise au point automatique
G03B 43/00 - Test du fonctionnement correct d'appareils photographiques ou de leurs pièces
G02B 7/08 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour lentilles avec mécanisme de mise au point ou pour faire varier le grossissement adaptés pour fonctionner en combinaison avec un mécanisme de télécommande
D<2 of a required scale for a normalised version of the ROI. The apparatus then fractionally downsamples and rotates downsampled information for a tile within the buffer to produce a respective normalised portion of the ROI at the required scale for the normalised ROI. Downsampled and rotated information is accumulated for each tile within a normalised ROI buffer for subsequent processing by the image processing apparatus.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06T 3/60 - Rotation d'une image entière ou d'une partie d'image
G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
A method and system of generating an adjustment parameter value for a control parameter to enhance a new image, which includes configuring a neural network, trained to restore image quality for a derivative image, to that of an earlier version of the derivative image, to generate as an output the adjustment parameter value, for the control parameter in response to input of data derived from the new image, and changing a control parameter of the new image, by generating the adjustment parameter value by calculating an inverse of the output value, and applying the adjustment parameter value to the control parameter of the new image so as to generate an enhanced image.
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
G06K 9/66 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques utilisant des comparaisons ou corrélations simultanées de signaux images avec une pluralité de références, p.ex. matrice de résistances avec des références réglables par une méthode adaptative, p.ex. en s'instruisant
G06N 3/00 - Agencements informatiques fondés sur des modèles biologiques
87.
Capturing and processing of images including occlusions focused on an image sensor by a lens stack array
Systems and methods for implementing array cameras configured to perform super-resolution processing to generate higher resolution super-resolved images using a plurality of captured images and lens stack arrays that can be utilized in array cameras are disclosed. An imaging device in accordance with one embodiment of the invention includes at least one imager array, and each imager in the array comprises a plurality of light sensing elements and a lens stack including at least one lens surface, where the lens stack is configured to form an image on the light sensing elements, control circuitry configured to capture images formed on the light sensing elements of each of the imagers, and a super-resolution processing module configured to generate at least one higher resolution super-resolved image using a plurality of the captured images.
H04N 5/365 - Traitement du bruit, p.ex. détection, correction, réduction ou élimination du bruit appliqué au bruit à motif fixe, p.ex. non-uniformité de la réponse
H04N 13/128 - Ajustement de la profondeur ou de la disparité
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
H04N 5/33 - Transformation des rayonnements infrarouges
H04N 5/341 - Extraction de données de pixels provenant d'un capteur d'images en agissant sur les circuits de balayage, p.ex. en modifiant le nombre de pixels ayant été échantillonnés ou à échantillonner
H04N 5/349 - Extraction de données de pixels provenant d'un capteur d'images en agissant sur les circuits de balayage, p.ex. en modifiant le nombre de pixels ayant été échantillonnés ou à échantillonner pour accroître la résolution en déplaçant le capteur par rapport à la scène
H04N 9/097 - Dispositions optiques associées aux dispositifs analyseurs, p.ex. pour partager des faisceaux, pour corriger la couleur
G06T 19/20 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie Édition d'images tridimensionnelles [3D], p.ex. modification de formes ou de couleurs, alignement d'objets ou positionnements de parties
H04N 9/09 - Générateurs de signaux d'image avec plusieurs têtes de lecture
H04N 9/73 - Circuits pour l'équilibrage des couleurs, p.ex. circuits pour équilibrer le blanc ou commande de la température de couleur
H04N 5/262 - Circuits de studio, p.ex. pour mélanger, commuter, changer le caractère de l'image, pour d'autres effets spéciaux
G06T 7/557 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir des champs de lumière, p.ex. de caméras plénoptiques
H04N 13/239 - Générateurs de signaux d’images utilisant des caméras à images stéréoscopiques utilisant deux capteurs d’images 2D dont la position relative est égale ou en correspondance à l’intervalle oculaire
G06T 7/50 - Récupération de la profondeur ou de la forme
Systems and methods for authenticating a biometric device using a trusted coordinating smart device in accordance with embodiments of the invention are disclosed. In one embodiment, a process for enrolling a configurable biometric device with a network service includes obtaining a device identifier (ID) of the configurable biometric device using a coordinating smart device, communicating the device ID from the coordinating smart device to a network service, communicating a first challenge based on a challenge-response authentication protocol from the network service to the coordinating smart device, communicating the first challenge and a response uniform resource locator (URL) from the coordinating smart device to the configurable biometric device, generating a first response to the first challenge and communicating the first response to the network service utilizing the response URL, receiving a secure channel key by the coordinating smart device from the network service, communicating the secure channel key from the coordinating smart device to the configurable biometric device, performing a biometric enrollment process using the configurable biometric device including capturing biometric information from a user, and creating a secure communication link between the configurable biometric device and the network service using the secure channel key when the first response satisfies the challenge-response authentication protocol.
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
G06F 21/32 - Authentification de l’utilisateur par données biométriques, p.ex. empreintes digitales, balayages de l’iris ou empreintes vocales
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
A method for correcting an image divides an output image into a grid with vertical sections of width smaller than the image width but wide enough to allow efficient bursts when writing distortion corrected line sections into memory. A distortion correction engine includes a relatively small amount of memory for an input image buffer but without requiring unduly complex control.The input image buffer accommodates enough lines of an input image to cover the distortion of a single most vertically distorted line section of the input image. The memory required for the input image buffer can be significantly less than would be required to store all the lines of a distorted input image spanning a maximal distortion of a complete line within the input image.
Systems and methods for implementing array camera configurations that include a plurality of constituent array cameras, where each constituent array camera provides a distinct field of view and/or a distinct viewing direction, are described. In several embodiments, image data captured by the constituent array cameras is used to synthesize multiple images that are subsequently blended. In a number of embodiments, the blended images include a foveated region. In certain embodiments, the blended images possess a wider field of view than the fields of view of the multiple images.
H04N 5/369 - Transformation d'informations lumineuses ou analogues en informations électriques utilisant des capteurs d'images à l'état solide [capteurs SSIS] circuits associés à cette dernière
H04N 5/247 - Disposition des caméras de télévision
H04N 13/243 - Générateurs de signaux d’images utilisant des caméras à images stéréoscopiques utilisant au moins trois capteurs d’images 2D
G06T 7/557 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir des champs de lumière, p.ex. de caméras plénoptiques
G06T 3/40 - Changement d'échelle d'une image entière ou d'une partie d'image
H04N 17/00 - Diagnostic, test ou mesure, ou leurs détails, pour les systèmes de télévision
G02B 13/02 - Télé-objectifs photographiques, c. à d. systèmes du type + — dans lesquels la distance du sommet de l'angle avant au plan de l'image est inférieure à la distance focale équivalente
H04N 13/232 - Générateurs de signaux d’images utilisant des caméras à images stéréoscopiques utilisant un seul capteur d’images 2D utilisant des lentilles du type œil de mouche, p.ex. dispositions de lentilles circulaires
91.
Stereoscopic (3D) panorama creation on handheld device
A technique of generating a stereoscopic panorama image includes panning a portable camera device, and acquiring multiple image frames. Multiple at least partially overlapping image frames are acquired of portions of the scene. The method involves registering the image frames, including determining displacements of the imaging device between acquisitions of image frames. Multiple panorama images are generated including joining image frames of the scene according to spatial relationships and determining stereoscopic counterpart relationships between the multiple panorama images. The multiple panorama images are processed based on the stereoscopic counterpart relationships to form a stereoscopic panorama image.
Systems with an array camera augmented with a conventional camera in accordance with embodiments of the invention are disclosed. In some embodiments, the array camera is used to capture a first set of image data of a scene and a conventional camera is used to capture a second set of image data for the scene. An object of interest is identified in the first set of image data. A first depth measurement for the object of interest is determined and compared to a predetermined threshold. If the first depth measurement is above the threshold, a second set of image data captured using the conventional camera is obtained. The object of interest is identified in the second set of image data and a second depth measurement for the object of interest is determined using at least a portion of the first set of image data and at least a portion of the second set of image data.
H04N 13/271 - Générateurs de signaux d’images où les signaux d’images générés comprennent des cartes de profondeur ou de disparité
G01P 3/38 - Dispositifs caractérisés par l'emploi de moyens optiques, p.ex. en utilisant la lumière infrarouge, visible ou ultraviolette en utilisant des moyens photographiques
H04N 13/243 - Générateurs de signaux d’images utilisant des caméras à images stéréoscopiques utilisant au moins trois capteurs d’images 2D
H04N 13/232 - Générateurs de signaux d’images utilisant des caméras à images stéréoscopiques utilisant un seul capteur d’images 2D utilisant des lentilles du type œil de mouche, p.ex. dispositions de lentilles circulaires
A peripheral processing device comprises a physical interface for connecting the processing device to a host computing device through a communications protocol. A local controller connected to local memory across an internal bus provides input/output access to data stored on the processing device to the host through a file system API. A neural processor comprises at least one network processing engine for processing a layer of a neural network according to a network configuration. A memory at least temporarily stores network configuration information, input image information, intermediate image information and output information produced by each network processing engine. The local controller is arranged to receive network configuration information through a file system API write command, to receive input image information through a file system API write command; and to write output information to the local memory for retrieval by the host through a file system API read command.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06N 3/06 - Réalisation physique, c. à d. mise en œuvre matérielle de réseaux neuronaux, de neurones ou de parties de neurone
A peripheral processing device comprises a physical interface for connecting the processing device to a host computing device through a communications protocol. A local controller connected to local memory across an internal bus provides input/output access to data stored on the processing device to the host through a file system API. A neural processor comprises at least one network processing engine for processing a layer of a neural network according to a network configuration. A memory at least temporarily stores network configuration information, input image information, intermediate image information and output information produced by each network processing engine. The local controller is arranged to receive network configuration information through a file system API write command, to receive input image information through a file system API write command; and to write output information to the local memory for retrieval by the host through a file system API read command.
G06N 3/063 - Réalisation physique, c. à d. mise en œuvre matérielle de réseaux neuronaux, de neurones ou de parties de neurone utilisant des moyens électroniques
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
95.
Systems and methods for estimating depth from projected texture using camera arrays
Systems and methods in accordance with embodiments of the invention estimate depth from projected texture using camera arrays. One embodiment of the invention includes: at least one two-dimensional array of cameras comprising a plurality of cameras; an illumination system configured to illuminate a scene with a projected texture; a processor; and memory containing an image processing pipeline application and an illumination system controller application. In addition, the illumination system controller application directs the processor to control the illumination system to illuminate a scene with a projected texture. Furthermore, the image processing pipeline application directs the processor to: utilize the illumination system controller application to control the illumination system to illuminate a scene with a projected texture capture a set of images of the scene illuminated with the projected texture; determining depth estimates for pixel locations in an image from a reference viewpoint using at least a subset of the set of images. Also, generating a depth estimate for a given pixel location in the image from the reference viewpoint includes: identifying pixels in the at least a subset of the set of images that correspond to the given pixel location in the image from the reference viewpoint based upon expected disparity at a plurality of depths along a plurality of epipolar lines aligned at different angles; comparing the similarity of the corresponding pixels identified at each of the plurality of depths; and selecting the depth from the plurality of depths at which the identified corresponding pixels have the highest degree of similarity as a depth estimate for the given pixel location in the image from the reference viewpoint.
G01B 11/22 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer la profondeur
G01B 11/25 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer des contours ou des courbes en projetant un motif, p.ex. des franges de moiré, sur l'objet
G06T 7/521 - Récupération de la profondeur ou de la forme à partir de la projection de lumière structurée
G06T 7/593 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir d’images stéréo
G06T 7/557 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir des champs de lumière, p.ex. de caméras plénoptiques
Systems and methods for hybrid depth regularization in accordance with various embodiments of the invention are disclosed. In one embodiment of the invention, a depth sensing system comprises a plurality of cameras; a processor; and a memory containing an image processing application. The image processing application may direct the processor to obtain image data for a plurality of images from multiple viewpoints, the image data comprising a reference image and at least one alternate view image; generate a raw depth map using a first depth estimation process, and a confidence map; and generate a regularized depth map. The regularized depth map may be generated by computing a secondary depth map using a second different depth estimation process; and computing a composite depth map by selecting depth estimates from the raw depth map and the secondary depth map based on the confidence map.
An image acquisition method operates in a hand held image acquisition device with a camera. A first image of a scene is obtained with the camera at a nominal exposure level. A number of relatively bright pixels and a number of relatively dark pixels within the first image are determined. Based on the number of relatively bright pixels, a negative exposure adjustment is determined and based on the number of relatively dark pixels, a positive exposure adjustment is determined. Respective images are acquired at the nominal exposure level; with the negative exposure adjustment; and with the positive exposure adjustment as component images for high dynamic range (HDR) image of the scene.
Systems and methods in accordance with embodiments of this invention perform depth regularization and semiautomatic interactive matting using images. In an embodiment of the invention, the image processing pipeline application directs a processor to receive (i) an image (ii) an initial depth map corresponding to the depths of pixels within the image, regularize the initial depth map into a dense depth map using depth values of known pixels to compute depth values of unknown pixels, determine an object of interest to be extracted from the image, generate an initial trimap using the dense depth map and the object of interest to be extracted from the image, and apply color image matting to unknown regions of the initial trimap to generate a matte for image matting.
Systems and methods for reducing motion blur in images or video in ultra low light with array cameras in accordance with embodiments of the invention are disclosed. In one embodiment, a method for synthesizing an image from multiple images captured using an array camera includes capturing image data using active cameras within an array camera, where the active cameras are configured to capture image data and the image data includes pixel brightness values that form alternate view images captured from different viewpoints, determining sets of corresponding pixels in the alternate view images where each pixel in a set of corresponding pixels is chosen from a different alternate view image, summing the pixel brightness values for corresponding pixels to create pixel brightness sums for pixel locations in an output image, and synthesizing an output image from the viewpoint of the output image using the pixel brightness sums.
A method for producing framing information for a set of N source images, each comprising an object region R, comprises scaling, translating and/or rotating images of the source images so that the object region is aligned. For a given image of the object aligned source images, at a given frame size, a given frame angle for a frame relative to the object aligned images and at a first candidate boundary position for the frame, the method determines if there is at least one position for a second boundary of the frame orthogonal to the first boundary where the frame lies within the image and the frame encloses the object region. If so, counters associated with the first candidate boundary position are incremented. Responsive to any counter meeting a threshold value,K≤N, for the source images, framing is indicated as possible at the given frame size, frame angle, first candidate boundary position and any position for the second boundary associated with the threshold meeting counter. Otherwise, another image can be chosen and the process repeated.
