Systems, methods, and apparatuses are described for capturing panoramic images and positioning virtual objects on a device screen, using a device having a static camera and an adjustable camera. To generate a panoramic image, the device moves the field of view of the adjustable camera by moving a corresponding MEMS mirror. The device then captures a first image using the static camera, and a second image using the adjustable camera, and generates a panoramic image by combining the first and second images. To position a virtual object, the device captures a first image using the static camera, and determines that there are insufficient visual features in the first image for positioning. The device moves the field of view of the adjustable camera by moving the corresponding MEMS mirror, and captures a second image. Visual features from the second image are then used to position the virtual object.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G02B 26/08 - Optical devices or arrangements for the control of light using movable or deformable optical elements for controlling the direction of light
Systems and methods are provided for enabling improved image capture at a computing device comprising a plurality of cameras. First and second capture streams, from respective first and second cameras of a computing device, are received at the computing device, wherein the first and second cameras face in different directions. A region of the first capture stream to include as an overlay over a portion of the second capture stream is identified. It is determined that a combined frame comprising a frame from the second capture stream with an overlay from the region of the first capture stream meets threshold criterion based on image component analysis, and, in response to the determining, an image based on the combined frame is stored in a non-transitory memory.
Systems and methods are provided for improving image item editing. An image item is selected at a computing device and with an editing application, and a preferred editing option to apply to the image item is identified via a user profile. The preferred editing option is determined based on historic editing actions for a plurality of different image items. An icon for applying the preferred editing option to the image item is generated for display in a user interface of the editing application. User input associated with the icon is received, and the preferred editing option is applied to the image item.
G06F 3/04845 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour
G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
G06T 5/50 - Image enhancement or restoration using two or more images, e.g. averaging or subtraction
Systems, methods and apparatuses are described herein for accessing image data that comprises a plurality of macropixels, wherein the image data may be generated using a device comprising a lenslet array. The image data may be decomposed into a plurality of components using Kronecker product singular value decomposition (KP-SVD). Each component of the plurality of components may be encoded. Each encoded component of the plurality of components may be transmitted to cause display of reconstructed image data based on decoding each encoded component of the plurality of components.
H04N 21/2343 - Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs involving reformatting operations of video signals for distribution or compliance with end-user requests or end-user device requirements
H04N 21/4402 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs involving reformatting operations of video signals for household redistribution, storage or real-time display
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.
Systems and methods are described for enabling a lensless camera having an image sensor and a mask to be positioned behind a display screen of a device, which allows for the device to have an increased screen-to-body ratio. The image sensor captures an image based on the light that travels through the display screen and the mask. The display screen may include portions between pixel elements that allow light to pass through. The mask may include a pattern, such as an opaque material with portions that allow light to pass through from the portions of the display layer to the image sensor. The image captured by the image sensor may be indiscernible to humans. The system may utilize a trained machine learning model to reconstruct the image, using data about the pattern of the mask, so humans may visually recognize features in the image.
Systems and methods are described for enabling a lensless camera having an image sensor and a mask to be positioned behind a display screen of a device, which allows for the device to have an increased screen-to-body ratio. The image sensor captures an image based on the light that travels through the display screen and the mask. The display screen may include portions between pixel elements that allow light to pass through. The mask may include a pattern, such as an opaque material with portions that allow light to pass through from the portions of the display layer to the image sensor. The image captured by the image sensor may be indiscernible to humans. The system may utilize a trained machine learning model to reconstruct the image, using data about the pattern of the mask, so humans may visually recognize features in the image.
G06F 1/16 - Constructional details or arrangements
G09G 3/34 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix by control of light from an independent source
H04M 1/02 - Constructional features of telephone sets
H04N 23/955 - Computational photography systems, e.g. light-field imaging systems for lensless imaging
8.
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 - Image signal generators for generating image signals corresponding to three or more geometrical viewpoints, e.g. multi-view systems
H04N 17/00 - Diagnosis, testing or measuring for television systems or their details
H04N 17/02 - Diagnosis, testing or measuring for television systems or their details for colour television signals
H04N 23/667 - Camera operation mode switching, e.g. between still and video, sport and normal or high and low resolution modes
H04N 23/951 - Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
9.
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 13/239 - Image signal generators using stereoscopic image cameras using two 2D image sensors having a relative position equal to or related to the interocular distance
H04N 23/11 - Cameras or camera modules comprising electronic image sensorsControl thereof for generating image signals from different wavelengths for generating image signals from visible and infrared light wavelengths
H04N 23/13 - Cameras or camera modules comprising electronic image sensorsControl thereof for generating image signals from different wavelengths with multiple sensors
H04N 23/16 - Optical arrangements associated therewith, e.g. for beam-splitting or for colour correction
H04N 23/45 - Cameras or camera modules comprising electronic image sensorsControl thereof for generating image signals from two or more image sensors being of different type or operating in different modes, e.g. with a CMOS sensor for moving images in combination with a charge-coupled device [CCD] for still images
H04N 23/54 - Mounting of pick-up tubes, electronic image sensors, deviation or focusing coils
H04N 23/55 - Optical parts specially adapted for electronic image sensorsMounting thereof
H04N 23/69 - Control of means for changing angle of the field of view, e.g. optical zoom objectives or electronic zooming
H04N 23/698 - Control of cameras or camera modules for achieving an enlarged field of view, e.g. panoramic image capture
H04N 23/88 - Camera processing pipelinesComponents thereof for processing colour signals for colour balance, e.g. white-balance circuits or colour temperature control
H04N 23/951 - Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
H04N 25/13 - Arrangement of colour filter arrays [CFA]Filter mosaics characterised by the spectral characteristics of the filter elements
H04N 25/131 - Arrangement of colour filter arrays [CFA]Filter mosaics characterised by the spectral characteristics of the filter elements including elements passing infrared wavelengths
H04N 25/133 - Arrangement of colour filter arrays [CFA]Filter mosaics characterised by the spectral characteristics of the filter elements including elements passing panchromatic light, e.g. filters passing white light
H04N 25/40 - Extracting pixel data from image sensors by controlling scanning circuits, e.g. by modifying the number of pixels sampled or to be sampled
H04N 25/48 - Increasing resolution by shifting the sensor relative to the scene
H04N 25/581 - Control of the dynamic range involving two or more exposures acquired simultaneously
H04N 25/60 - Noise processing, e.g. detecting, correcting, reducing or removing noise
H04N 25/67 - Noise processing, e.g. detecting, correcting, reducing or removing noise applied to fixed-pattern noise, e.g. non-uniformity of response
H04N 25/705 - Pixels for depth measurement, e.g. RGBZ
H04N 25/79 - Arrangements of circuitry being divided between different or multiple substrates, chips or circuit boards, e.g. stacked image sensors
10.
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 7/44 - Analysis of texture based on statistical description of texture using image operators, e.g. filters, edge density metrics or local histograms
11.
AUTOMATED RADIAL BLURRING BASED ON SALIENCY AND CO-SALIENCY
Systems and methods are described for automatically performing automated radial blurring. A plurality of images may be accessed, and saliency parameters may be determined based on at least one of the plurality of images. Co-saliency parameters may be determined based on the plurality of images. A region of interest (ROI) in the at least one of the plurality of images may be determined based on the saliency parameters and the co-saliency parameters. Automated radial blurring of the at least one of the plurality of images may be performed based on the identified ROI.
Systems and methods in accordance with embodiments of the invention are configured to decode images containing an image of a scene and a corresponding depth map. A depth-based effect is applied to the image to generate a synthetic image of the scene. The synthetic image can be encoded into a new image file that contains metadata associated with the depth-based effect. In many embodiments, the original decoded image has a different depth-based effect applied to it with respect to the synthetic image.
H04N 13/178 - Metadata, e.g. disparity information
G06T 3/4007 - Scaling of whole images or parts thereof, e.g. expanding or contracting based on interpolation, e.g. bilinear interpolation
G06T 3/4053 - Scaling of whole images or parts thereof, e.g. expanding or contracting based on super-resolution, i.e. the output image resolution being higher than the sensor resolution
H04N 13/161 - Encoding, multiplexing or demultiplexing different image signal components
H04N 13/243 - Image signal generators using stereoscopic image cameras using three or more 2D image sensors
H04N 13/271 - Image signal generators wherein the generated image signals comprise depth maps or disparity maps
H04N 19/136 - Incoming video signal characteristics or properties
H04N 19/597 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding specially adapted for multi-view video sequence encoding
H04N 19/625 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using discrete cosine transform [DCT]
H04N 19/85 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression
13.
Systems and Methods for Estimating Depth and Visibility from a Reference Viewpoint for Pixels in a Set of Images Captured from Different Viewpoints
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 - Image signal generators using stereoscopic image cameras using a single 2D image sensor using fly-eye lenses, e.g. arrangements of circular lenses
H04N 13/243 - Image signal generators using stereoscopic image cameras using three or more 2D image sensors
H04N 23/16 - Optical arrangements associated therewith, e.g. for beam-splitting or for colour correction
14.
SYSTEMS AND METHODS FOR CAPTURING AN IMAGE OF A DESIRED MOMENT
Systems, methods and apparatuses are described for determining an image that corresponds to a received input instruction. Input may be received which comprises an instruction for an image sensor to capture at least one image of a subject and the instruction comprising at least one criterion for the at least one image of the subject. An image sensor may capture, based on the instruction, captured images of the subject. An instruction vector may be determined based on the instruction, and a captured image vector for each of the captured images of the subject may be determined. At least one captured image vector of the captured images and the instruction vector may be compared to determine a corresponding image from the captured images, and the corresponding image may be provided.
Systems, methods and apparatuses are described for determining an image that corresponds to a received input instruction. Input may be received which comprises an instruction for an image sensor to capture at least one image of a subject and the instruction comprising at least one criterion for the at least one image of the subject. An image sensor may capture, based on the instruction, captured images of the subject. An instruction vector may be determined based on the instruction, and a captured image vector for each of the captured images of the subject may be determined. At least one captured image vector of the captured images and the instruction vector may be compared to determine a corresponding image from the captured images, and the corresponding image may be provided.
Systems, methods, and apparatuses are provided herein for changing the positions and/or shapes of microlenses of a light field camera to generate light field images with enhanced depth of field and/or dynamic range. This may be accomplished by a light field camera determining a plurality of focus measurements for a plurality of microlenses, wherein one or more of the plurality of microlenses vary in distance from a main lens of the light field camera. The light field camera may use the plurality of focus measurements to determine a microlens of the plurality of microlenses that captures information that is the most focused. The light field camera can then determine defocus functions for the microlenses that are not capturing information that is the most focused. The light field camera can then generate a light field image using the determined defocus functions and the information captured by the plurality of microlenses.
Systems, methods, and apparatuses are provided herein for changing the positions and/or shapes of microlenses of a light field camera to generate light field images with enhanced depth of field and/or dynamic range. This may be accomplished by a light field camera determining a plurality of focus measurements for a plurality of microlenses, wherein one or more of the plurality of microlenses vary in distance from a main lens of the light field camera. The light field camera may use the plurality of focus measurements to determine a microlens of the plurality of microlenses that captures information that is the most focused. The light field camera can then determine defocus functions for the microlenses that are not capturing information that is the most focused. The light field camera can then generate a light field image using the determined defocus functions and the information captured by the plurality of microlenses.
A hand-held digital camera has a touch-sensitive display screen (“touch screen”) for image preview and user control of the camera, and a user-selectable panorama mode. Upon entering panorama mode the camera superimposes upon the touch screen a horizontal rectangular bar whose width and/or height are user-adjustable by interaction with the touch screen to select a desired horizontal sweep angle. After the sweep angle is set the camera automatically captures successive horizontally overlapping images during a sweep of the device through the selected sweep angle. Subsequently the camera synthesises a panoramic image from the successively captured images, the panoramic image having a width corresponding to the selected sweep angle.
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.
G06T 3/4053 - Scaling of whole images or parts thereof, e.g. expanding or contracting based on super-resolution, i.e. the output image resolution being higher than the sensor resolution
G06T 3/4007 - Scaling of whole images or parts thereof, e.g. expanding or contracting based on interpolation, e.g. bilinear interpolation
G06T 3/4076 - Scaling of whole images or parts thereof, e.g. expanding or contracting based on super-resolution, i.e. the output image resolution being higher than the sensor resolution using the original low-resolution images to iteratively correct the high-resolution images
H04N 13/139 - Format conversion, e.g. of frame-rate or size
H04N 23/62 - Control of parameters via user interfaces
H04N 23/951 - Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
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.
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 - Image signal generators using stereoscopic image cameras using two 2D image sensors having a relative position equal to or related to the interocular distance
H04N 23/11 - Cameras or camera modules comprising electronic image sensorsControl thereof for generating image signals from different wavelengths for generating image signals from visible and infrared light wavelengths
H04N 23/13 - Cameras or camera modules comprising electronic image sensorsControl thereof for generating image signals from different wavelengths with multiple sensors
H04N 23/16 - Optical arrangements associated therewith, e.g. for beam-splitting or for colour correction
H04N 23/45 - Cameras or camera modules comprising electronic image sensorsControl thereof for generating image signals from two or more image sensors being of different type or operating in different modes, e.g. with a CMOS sensor for moving images in combination with a charge-coupled device [CCD] for still images
H04N 23/54 - Mounting of pick-up tubes, electronic image sensors, deviation or focusing coils
H04N 23/55 - Optical parts specially adapted for electronic image sensorsMounting thereof
H04N 23/69 - Control of means for changing angle of the field of view, e.g. optical zoom objectives or electronic zooming
H04N 23/698 - Control of cameras or camera modules for achieving an enlarged field of view, e.g. panoramic image capture
H04N 23/88 - Camera processing pipelinesComponents thereof for processing colour signals for colour balance, e.g. white-balance circuits or colour temperature control
H04N 23/951 - Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
H04N 25/40 - Extracting pixel data from image sensors by controlling scanning circuits, e.g. by modifying the number of pixels sampled or to be sampled
H04N 25/48 - Increasing resolution by shifting the sensor relative to the scene
H04N 25/581 - Control of the dynamic range involving two or more exposures acquired simultaneously
H04N 25/60 - Noise processing, e.g. detecting, correcting, reducing or removing noise
H04N 25/67 - Noise processing, e.g. detecting, correcting, reducing or removing noise applied to fixed-pattern noise, e.g. non-uniformity of response
H04N 25/705 - Pixels for depth measurement, e.g. RGBZ
H04N 25/79 - Arrangements of circuitry being divided between different or multiple substrates, chips or circuit boards, e.g. stacked image sensors
H04N 13/00 - Stereoscopic video systemsMulti-view video systemsDetails thereof
H04N 25/13 - Arrangement of colour filter arrays [CFA]Filter mosaics characterised by the spectral characteristics of the filter elements
H04N 25/131 - Arrangement of colour filter arrays [CFA]Filter mosaics characterised by the spectral characteristics of the filter elements including elements passing infrared wavelengths
H04N 25/133 - Arrangement of colour filter arrays [CFA]Filter mosaics characterised by the spectral characteristics of the filter elements including elements passing panchromatic light, e.g. filters passing white light
22.
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 13/239 - Image signal generators using stereoscopic image cameras using two 2D image sensors having a relative position equal to or related to the interocular distance
H04N 23/11 - Cameras or camera modules comprising electronic image sensorsControl thereof for generating image signals from different wavelengths for generating image signals from visible and infrared light wavelengths
H04N 23/13 - Cameras or camera modules comprising electronic image sensorsControl thereof for generating image signals from different wavelengths with multiple sensors
H04N 23/16 - Optical arrangements associated therewith, e.g. for beam-splitting or for colour correction
H04N 23/45 - Cameras or camera modules comprising electronic image sensorsControl thereof for generating image signals from two or more image sensors being of different type or operating in different modes, e.g. with a CMOS sensor for moving images in combination with a charge-coupled device [CCD] for still images
H04N 23/54 - Mounting of pick-up tubes, electronic image sensors, deviation or focusing coils
H04N 23/55 - Optical parts specially adapted for electronic image sensorsMounting thereof
H04N 23/69 - Control of means for changing angle of the field of view, e.g. optical zoom objectives or electronic zooming
H04N 23/698 - Control of cameras or camera modules for achieving an enlarged field of view, e.g. panoramic image capture
H04N 23/88 - Camera processing pipelinesComponents thereof for processing colour signals for colour balance, e.g. white-balance circuits or colour temperature control
H04N 23/951 - Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
H04N 25/40 - Extracting pixel data from image sensors by controlling scanning circuits, e.g. by modifying the number of pixels sampled or to be sampled
H04N 25/48 - Increasing resolution by shifting the sensor relative to the scene
H04N 25/581 - Control of the dynamic range involving two or more exposures acquired simultaneously
H04N 25/60 - Noise processing, e.g. detecting, correcting, reducing or removing noise
H04N 25/67 - Noise processing, e.g. detecting, correcting, reducing or removing noise applied to fixed-pattern noise, e.g. non-uniformity of response
H04N 25/705 - Pixels for depth measurement, e.g. RGBZ
H04N 25/79 - Arrangements of circuitry being divided between different or multiple substrates, chips or circuit boards, e.g. stacked image sensors
H04N 13/00 - Stereoscopic video systemsMulti-view video systemsDetails thereof
H04N 25/13 - Arrangement of colour filter arrays [CFA]Filter mosaics characterised by the spectral characteristics of the filter elements
H04N 25/131 - Arrangement of colour filter arrays [CFA]Filter mosaics characterised by the spectral characteristics of the filter elements including elements passing infrared wavelengths
H04N 25/133 - Arrangement of colour filter arrays [CFA]Filter mosaics characterised by the spectral characteristics of the filter elements including elements passing panchromatic light, e.g. filters passing white light
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.
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 - Image signal generators for generating image signals corresponding to three or more geometrical viewpoints, e.g. multi-view systems
H04N 17/02 - Diagnosis, testing or measuring for television systems or their details for colour television signals
H04N 23/667 - Camera operation mode switching, e.g. between still and video, sport and normal or high and low resolution modes
H04N 23/951 - Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
25.
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.
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.
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 7/44 - Analysis of texture based on statistical description of texture using image operators, e.g. filters, edge density metrics or local histograms
28.
Systems and Methods for Estimating Depth from Projected Texture using Camera Arrays
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 - Measuring arrangements characterised by the use of optical techniques for measuring depth
G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object
G06T 7/521 - Depth or shape recovery from laser ranging, e.g. using interferometryDepth or shape recovery from the projection of structured light
G06T 7/593 - Depth or shape recovery from multiple images from stereo images
G06T 7/557 - Depth or shape recovery from multiple images from light fields, e.g. from plenoptic cameras
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.
G06T 7/593 - Depth or shape recovery from multiple images from stereo images
H04N 13/243 - Image signal generators using stereoscopic image cameras using three or more 2D image sensors
H04N 13/271 - Image signal generators wherein the generated image signals comprise depth maps or disparity maps
H04N 23/45 - Cameras or camera modules comprising electronic image sensorsControl thereof for generating image signals from two or more image sensors being of different type or operating in different modes, e.g. with a CMOS sensor for moving images in combination with a charge-coupled device [CCD] for still images
H04N 23/90 - Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums
H04N 5/222 - Studio circuitryStudio devicesStudio equipment
H04N 13/00 - Stereoscopic video systemsMulti-view video systemsDetails thereof
H04N 23/11 - Cameras or camera modules comprising electronic image sensorsControl thereof for generating image signals from different wavelengths for generating image signals from visible and infrared light wavelengths
H04N 23/56 - Cameras or camera modules comprising electronic image sensorsControl thereof provided with illuminating means
30.
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.
G06T 3/40 - Scaling of whole images or parts thereof, e.g. expanding or contracting
H04N 23/951 - Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
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.
G06T 7/557 - Depth or shape recovery from multiple images from light fields, e.g. from plenoptic cameras
H04N 13/239 - Image signal generators using stereoscopic image cameras using two 2D image sensors having a relative position equal to or related to the interocular distance
H04N 23/11 - Cameras or camera modules comprising electronic image sensorsControl thereof for generating image signals from different wavelengths for generating image signals from visible and infrared light wavelengths
H04N 23/13 - Cameras or camera modules comprising electronic image sensorsControl thereof for generating image signals from different wavelengths with multiple sensors
H04N 23/16 - Optical arrangements associated therewith, e.g. for beam-splitting or for colour correction
H04N 23/45 - Cameras or camera modules comprising electronic image sensorsControl thereof for generating image signals from two or more image sensors being of different type or operating in different modes, e.g. with a CMOS sensor for moving images in combination with a charge-coupled device [CCD] for still images
H04N 23/54 - Mounting of pick-up tubes, electronic image sensors, deviation or focusing coils
H04N 23/55 - Optical parts specially adapted for electronic image sensorsMounting thereof
H04N 23/69 - Control of means for changing angle of the field of view, e.g. optical zoom objectives or electronic zooming
H04N 23/88 - Camera processing pipelinesComponents thereof for processing colour signals for colour balance, e.g. white-balance circuits or colour temperature control
H04N 23/951 - Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
H04N 25/40 - Extracting pixel data from image sensors by controlling scanning circuits, e.g. by modifying the number of pixels sampled or to be sampled
H04N 25/48 - Increasing resolution by shifting the sensor relative to the scene
H04N 25/60 - Noise processing, e.g. detecting, correcting, reducing or removing noise
H04N 25/67 - Noise processing, e.g. detecting, correcting, reducing or removing noise applied to fixed-pattern noise, e.g. non-uniformity of response
H04N 25/79 - Arrangements of circuitry being divided between different or multiple substrates, chips or circuit boards, e.g. stacked image sensors
H04N 25/581 - Control of the dynamic range involving two or more exposures acquired simultaneously
H04N 25/705 - Pixels for depth measurement, e.g. RGBZ
G06T 19/20 - Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
H04N 5/262 - Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects
H04N 25/131 - Arrangement of colour filter arrays [CFA]Filter mosaics characterised by the spectral characteristics of the filter elements including elements passing infrared wavelengths
H04N 25/133 - Arrangement of colour filter arrays [CFA]Filter mosaics characterised by the spectral characteristics of the filter elements including elements passing panchromatic light, e.g. filters passing white light
H04N 25/13 - Arrangement of colour filter arrays [CFA]Filter mosaics characterised by the spectral characteristics of the filter elements
H04N 13/00 - Stereoscopic video systemsMulti-view video systemsDetails thereof
An approach for an iris liveness detection is provided. A plurality of image pairs is acquired using one or more image sensors of a mobile device. A particular image pair is selected from the plurality of image pairs, and a hyperspectral image is generated for the particular image pair. Based on, at least in part, the hyperspectral image, a particular feature vector for the eye-iris region depicted in the particular image pair is generated, and one or more trained model feature vectors generated for facial features of a particular user of the device are retrieved. Based on, at least in part, the particular feature vector and the one or more trained model feature vectors, a distance metric is determined and compared with a threshold. If the distance metric exceeds the threshold, then a first message indicating that the plurality of image pairs fails to depict the particular user is generated. It is also determined whether at least one characteristic, of one or more characteristics determined for NIR images, changes from image-to-image by at least a second threshold. If so, then a second message is generated to indicate that the plurality of image pairs depicts the particular user of a mobile device. The second message may also indicate that an authentication of an owner to the mobile device was successful. Otherwise, a third message is generated to indicate that a presentation attack on the mobile device is in progress.
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.
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 hand-held digital camera has a touch-sensitive display screen (“touch screen”) for image preview and user control of the camera, and a user-selectable panorama mode. Upon entering panorama mode the camera superimposes upon the touch screen a horizontal rectangular bar whose width and/or height are user-adjustable by interaction with the touch screen to select a desired horizontal sweep angle. After the sweep angle is set the camera automatically captures successive horizontally overlapping images during a sweep of the device through the selected sweep angle. Subsequently the camera synthesizes a panoramic image from the successively captured images, the panoramic image having a width corresponding to the selected sweep angle.
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.
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 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.
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 - Image signal generators using stereoscopic image cameras using a single 2D image sensor using fly-eye lenses, e.g. arrangements of circular lenses
H04N 13/243 - Image signal generators using stereoscopic image cameras using three or more 2D image sensors
H04N 23/16 - Optical arrangements associated therewith, e.g. for beam-splitting or for colour correction
H04N 13/00 - Stereoscopic video systemsMulti-view video systemsDetails thereof
An approach for an iris liveness detection is provided. A plurality of image pairs is acquired using one or more image sensors of a mobile device. A particular image pair is selected from the plurality of image pairs, and a hyperspectral image is generated for the particular image pair. Based on, at least in part, the hyperspectral image, a particular feature vector for the eye-iris region depicted in the particular image pair is generated, and one or more trained model feature vectors generated for facial features of a particular user of the device are retrieved. Based on, at least in part, the particular feature vector and the one or more trained model feature vectors, a distance metric is determined and compared with a threshold. If the distance metric exceeds the threshold, then a first message indicating that the plurality of image pairs fails to depict the particular user is generated. It is also determined whether at least one characteristic, of one or more characteristics determined for NIR images, changes from image-to-image by at least a second threshold. If so, then a second message is generated to indicate that the plurality of image pairs depicts the particular user of a mobile device. The second message may also indicate that an authentication of an owner to the mobile device was successful. Otherwise, a third message is generated to indicate that a presentation attack on the mobile device is in progress.
A method of image processing within an image acquisition device. In one embodiment an image including one or more face regions is acquired and one or more iris regions are identified within the one or more face regions. The one or more iris regions are analyzed to identify any iris region containing an iris pattern that poses a risk of biometrically identifying a subject within the image. Responsive to identifying any such iris region, a respective substitute iris region, containing an iris pattern distinct from the identified iris pattern to avoid identifying the subject within the image, is determined and the identified iris region is replaced with the substitute iris region in the original image.
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.
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.
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 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/32 - Aligning or centering of the image pick-up or image-field
H04N 5/232 - Devices for controlling television cameras, e.g. remote control
H04N 5/235 - Circuitry for compensating for variation in the brightness of the object
H04N 5/345 - Extracting pixel data from an image sensor by controlling scanning circuits, e.g. by modifying the number of pixels having been sampled or to be sampled by partially reading an SSIS array
H04N 5/347 - Extracting pixel data from an image sensor by controlling scanning circuits, e.g. by modifying the number of pixels having been sampled or to be sampled by combining or binning pixels in SSIS
H04N 5/77 - Interface circuits between an apparatus for recording and another apparatus between a recording apparatus and a television camera
H04N 9/804 - Transformation of the television signal for recording, e.g. modulation, frequency changingInverse transformation for playback involving pulse code modulation of the colour picture signal components
An approach for an iris liveness detection is provided. A plurality of image pairs is acquired using one or more image sensors of a mobile device. A particular image pair is selected from the plurality of image pairs, and a hyperspectral image is generated for the particular image pair. Based on, at least in part, the hyperspectral image, a particular feature vector for the eye-iris region depicted in the particular image pair is generated, and one or more trained model feature vectors generated for facial features of a particular user of the device are retrieved. Based on, at least in part, the particular feature vector and the one or more trained model feature vectors, a distance metric is determined and compared with a threshold. If the distance metric exceeds the threshold, then a first message indicating that the plurality of image pairs fails to depict the particular user is generated. It is also determined whether at least one characteristic, of one or more characteristics determined for NIR images, changes from image-to-image by at least a second threshold. If so, then a second message is generated to indicate that the plurality of image pairs depicts the particular user of a mobile device. The second message may also indicate that an authentication of an owner to the mobile device was successful. Otherwise, a third message is generated to indicate that a presentation attack on the mobile device is in progress.
A hand-held digital camera has a touch-sensitive display screen (“touch screen”) for image preview and user control of the camera, and a user-selectable panorama mode. Upon entering panorama mode the camera superimposes upon the touch screen a horizontal rectangular bar whose width and/or height are user-adjustable by interaction with the touch screen to select a desired horizontal sweep angle. After the sweep angle is set the camera automatically captures successive horizontally overlapping images during a sweep of the device through the selected sweep angle. Subsequently the camera synthesises a panoramic image from the successively captured images, the panoramic image having a width corresponding to the selected sweep angle.
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 - Depth or shape recovery from multiple images from stereo images
G06T 7/44 - Analysis of texture based on statistical description of texture using image operators, e.g. filters, edge density metrics or local histograms
A method for acquiring an image comprises acquiring a first image frame including a region containing a subject at a first focus position; determining a first sharpness of the subject within the first image frame; identifying an imaged subject size within the first image frame; determining a second focus position based on the imaged subject size; acquiring a second image frame at the second focus position; and determining a second sharpness of the subject within the second image frame. A sharpness threshold is determined as a function of image acquisition parameters for the first and/or second image frame. Responsive to the second sharpness not exceeding the first sharpness and the sharpness threshold, camera motion parameters and/or subject motion parameters for the second image frame are determined before performing a focus sweep to determine an optimal focus position for the subject.
A hand-held digital camera has a touch-sensitive display screen (“touch screen”) for image preview and user control of the camera, and a user-selectable panorama mode. Upon entering panorama mode the camera superimposes upon the touch screen a horizontal rectangular bar whose width and/or height are user-adjustable by interaction with the touch screen to select a desired horizontal sweep angle. After the sweep angle is set the camera automatically captures successive horizontally overlapping images during a sweep of the device through the selected sweep angle. Subsequently the camera synthesizes a panoramic image from the successively captured images, the panoramic image having a width corresponding to the selected sweep angle.
A method for acquiring an image comprises acquiring a first image frame including a region containing a subject at a first focus position; determining a first sharpness of the subject within the first image frame; identifying an imaged subject size within the first image frame; determining a second focus position based on the imaged subject size; acquiring a second image frame at the second focus position; and determining a second sharpness of the subject within the second image frame. A sharpness threshold is determined as a function of image acquisition parameters for the first and/or second image frame. Responsive to the second sharpness not exceeding the first sharpness and the sharpness threshold, camera motion parameters and/or subject motion parameters for the second image frame are determined before performing a focus sweep to determine an optimal focus position for the subject.
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 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/32 - Aligning or centering of the image pick-up or image-field
H04N 5/232 - Devices for controlling television cameras, e.g. remote control
H04N 5/235 - Circuitry for compensating for variation in the brightness of the object
H04N 5/272 - Means for inserting a foreground image in a background image, i.e. inlay, outlay
H04N 5/345 - Extracting pixel data from an image sensor by controlling scanning circuits, e.g. by modifying the number of pixels having been sampled or to be sampled by partially reading an SSIS array
H04N 5/347 - Extracting pixel data from an image sensor by controlling scanning circuits, e.g. by modifying the number of pixels having been sampled or to be sampled by combining or binning pixels in SSIS
H04N 5/77 - Interface circuits between an apparatus for recording and another apparatus between a recording apparatus and a television camera
H04N 9/804 - Transformation of the television signal for recording, e.g. modulation, frequency changingInverse transformation for playback involving pulse code modulation of the colour picture signal components
G06K 9/46 - Extraction of features or characteristics of the image
G06K 9/48 - Extraction of features or characteristics of the image by coding the contour of the pattern
G06T 3/40 - Scaling of whole images or parts thereof, e.g. expanding or contracting
In one embodiment, a gimbal adjustment system and an associated method for adjusting the position of an object. The system comprises a base, a plate and a shaft including a pivot attached to the plate. The pivot has a point of contact with the plate in a joint about which the plate is rotatable. Magnetic elements are positioned on the base and the plate to stabilize or rotate the plate. The object may be an optical unit attached to the plate. A combination comprising the plate, optical unit and magnetic elements may form a gimbaled assembly having a center of mass in the joint.
G02B 27/64 - Imaging systems using optical elements for stabilisation of the lateral and angular position of the image
H02K 33/12 - Motors with reciprocating, oscillating or vibrating magnet, armature or coil system with armatures moving in alternate directions by alternate energisation of two coil systems
G03B 5/04 - Vertical adjustment of lensRising fronts
A method of image processing within an image acquisition device. In one embodiment an image including one or more face regions is acquired and one or more iris regions are identified within the one or more face regions. The one or more iris regions are analyzed to identify any iris region containing an iris pattern that poses a risk of biometrically identifying a subject within the image. Responsive to identifying any such iris region, a respective substitute iris region, containing an iris pattern distinct from the identified iris pattern to avoid identifying the subject within the image, is determined and the identified iris region is replaced with the substitute iris region in the original image.
An image acquisition system for acquiring iris images for use in biometric recognition of a subject includes an optical system comprising a cluster of at least 2 lenses arranged in front of a common image sensor with each lens optical axis in parallel spaced apart relationship. Each lens has a fixed focus and a different aperture to provide a respective angular field of view. The lens with the closest focus has the smallest aperture and the lens with the farthest focus has the largest aperture so that iris images can be acquired across a focal range of at least from 200 mm to 300 mm.
A method for calibrating an image capture device comprises mounting at least one sample device from a batch for movement through a plurality of orientations relative to a horizontal plane. For a given orientation, the sample device is focused at a sequence of positions, each position being at a respective focus distance from the device. A lens actuator setting is recorded for the sample device at each position. This is repeated at a plurality of distinct orientations of the sample device. Respective relationships are determined between lens actuator settings at any given position for distinct orientations from the plurality of distinct orientations and actuator settings at a selected orientation of the plurality of distinct orientations. Lens actuator settings for the image capture device to be calibrated are recorded at least at two points of interest (POI), each a specified focus distance from the device with the image capture device positioned at the selected orientation. The image capture device is calibrated for the plurality of distinct orientations based on the determined relationships and the recorded lens actuator settings.
H04N 17/02 - Diagnosis, testing or measuring for television systems or their details for colour television signals
H04N 17/00 - Diagnosis, testing or measuring for television systems or their details
G02B 7/28 - Systems for automatic generation of focusing signals
H04N 5/232 - Devices for controlling television cameras, e.g. remote control
G02B 7/10 - Mountings, adjusting means, or light-tight connections, for optical elements for lenses with mechanism for focusing or varying magnification by relative axial movement of several lenses, e.g. of varifocal objective lens
An approach for an iris liveness detection is provided. A plurality of image pairs is acquired using one or more image sensors of a mobile device. A particular image pair is selected from the plurality of image pairs, and a hyperspectral image is generated for the particular image pair. Based on, at least in part, the hyperspectral image, a particular feature vector for the eye-iris region depicted in the particular image pair is generated, and one or more trained model feature vectors generated for facial features of a particular user of the device are retrieved. Based on, at least in part, the particular feature vector and the one or more trained model feature vectors, a distance metric is determined and compared with a threshold. If the distance metric exceeds the threshold, then a first message indicating that the plurality of image pairs fails to depict the particular user is generated. It is also determined whether at least one characteristic, of one or more characteristics determined for NIR images, changes from image-to-image by at least a second threshold. If so, then a second message is generated to indicate that the plurality of image pairs depicts the particular user of a mobile device. The second message may also indicate that an authentication of an owner to the mobile device was successful. Otherwise, a third message is generated to indicate that a presentation attack on the mobile device is in progress.
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.
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.
An optical system for an image acquisition device comprises an image sensor comprising an array of pixels including pixels sensitive to IR wavelengths for acquiring an image. A lens assembly includes a collecting lens surface with an optical axis, the lens assembly being arranged to focus IR light received from a given object distance on the sensor surface. The lens assembly includes at least a first reflective surface for reflecting collected light along an axis transverse to the optical axis so that a length of the optical system along the optical axis is reduced by comparison to a focal length of the lens assembly.
H04N 5/232 - Devices for controlling television cameras, e.g. remote control
G02B 7/04 - Mountings, adjusting means, or light-tight connections, for optical elements for lenses with mechanism for focusing or varying magnification
A method of processing an image comprises: acquiring an image of a scene including an object having a recognizable feature. A lens actuator setting providing a maximum sharpness for a region of the image including the object and a lens displacement corresponding to the lens actuator setting are determined. A distance to the object based on the lens displacement is calculated. A dimension of the feature as a function of the distance to the object, the imaged object size and a focal length of a lens assembly with which the image was acquired, is determined. The determined dimension of the feature is employed instead of an assumed dimension of the feature for subsequent processing of images of the scene including the object.
G02B 7/09 - Mountings, adjusting means, or light-tight connections, for optical elements for lenses with mechanism for focusing or varying magnification adapted for automatic focusing or varying magnification
G01B 11/14 - Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
61.
Foreground / background separation in digital images
A method for providing improved foreground/background separation in a digital image of a scene is disclosed. The method comprises providing a first map comprising one or more regions provisionally defined as one of foreground or background within the digital image; and providing a subject profile corresponding to a region of interest of the digital image. The provisionally defined regions are compared with the subject profile to determine if any of the regions intersect with the profile region. The definition of one or more of the regions in the map is changed based on the comparison.
A hand-held digital camera has a touch-sensitive display screen (“touch screen”) for image preview and user control of the camera, and a user-selectable panorama mode. Upon entering panorama mode the camera superimposes upon the touch screen a horizontal rectangular bar whose width and/or height are user-adjustable by interaction with the touch screen to select a desired horizontal sweep angle. After the sweep angle is set the camera automatically captures successive horizontally overlapping images during a sweep of the device through the selected sweep angle. Subsequently the camera synthesizes a panoramic image from the successively captured images, the panoramic image having a width corresponding to the selected sweep angle.
A method of image processing within an image acquisition device comprises: acquiring an image including one or more face regions and identifying one or more eye-iris regions within the one or more face regions. The one or more eye-iris regions are analyzed to identify any eye-iris region comprising an eye-iris pattern of sufficient quality to pose a risk of biometrically identifying a person within the image. Responsive to identifying any such eye-iris region, a respective substitute eye-iris region comprising an eye-iris pattern sufficiently distinct from the identified eye-iris pattern to avoid identifying the person within the image is determined, and the identified eye-iris region is replaced with the substitute eye-iris region in the original image.
A template matching module is configured to program a processor to apply multiple differently-tuned object detection classifier sets in parallel to a digital image to determine one or more of an object type, configuration, orientation, pose or illumination condition, and to dynamically switch between object detection templates to match a determined object type, configuration, orientation, pose, blur, exposure and/or directional illumination condition.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/62 - Methods or arrangements for recognition using electronic means
G06K 9/46 - Extraction of features or characteristics of the image
G06K 9/68 - Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of reference, e.g. addressable memory
A method of tracking faces in an image stream with a digital image acquisition device includes receiving images from an image stream including faces, calculating corresponding integral images, and applying different subsets of face detection rectangles to the integral images to provide sets of candidate regions. The different subsets include candidate face regions of different sizes and/or locations within the images. The different candidate face regions from different images of the image stream are each tracked.
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 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/32 - Aligning or centering of the image pick-up or image-field
H04N 5/232 - Devices for controlling television cameras, e.g. remote control
H04N 5/235 - Circuitry for compensating for variation in the brightness of the object
H04N 5/272 - Means for inserting a foreground image in a background image, i.e. inlay, outlay
H04N 5/345 - Extracting pixel data from an image sensor by controlling scanning circuits, e.g. by modifying the number of pixels having been sampled or to be sampled by partially reading an SSIS array
H04N 5/347 - Extracting pixel data from an image sensor by controlling scanning circuits, e.g. by modifying the number of pixels having been sampled or to be sampled by combining or binning pixels in SSIS
H04N 5/77 - Interface circuits between an apparatus for recording and another apparatus between a recording apparatus and a television camera
H04N 9/804 - Transformation of the television signal for recording, e.g. modulation, frequency changingInverse transformation for playback involving pulse code modulation of the colour picture signal components
G06K 9/46 - Extraction of features or characteristics of the image
G06K 9/48 - Extraction of features or characteristics of the image by coding the contour of the pattern
G06T 3/40 - Scaling of whole images or parts thereof, e.g. expanding or contracting
G06T 11/60 - Editing figures and textCombining figures or text
H04N 5/907 - Television signal recording using static stores, e.g. storage tubes or semiconductor memories
An image processing technique includes acquiring a main image of a scene and determining one or more facial regions in the main image. The facial regions are analyzed to determine if any of the facial regions includes a defect. A sequence of relatively low resolution images nominally of the same scene is also acquired. One or more sets of low resolution facial regions in the sequence of low resolution images are determined and analyzed for defects. Defect free facial regions of a set are combined to provide a high quality defect free facial region. At least a portion of any defective facial regions of the main image are corrected with image information from a corresponding high quality defect free facial region.
A forward interpolation approach is disclosed for enabling a second version of an image to be constructed from a first version of the image. According to one implementation, an input pixel from the first version of the image is forward mapped to the second version of the image to determine a set of candidate pixels that may be affected by the input pixel. Each candidate pixel is then backward mapped to the first version of the image to determine whether they are actually affected by the input pixel. For each candidate pixel that is actually affected by the input pixel, a pixel value is determined for that candidate pixel based at least in part upon the pixel value of the input pixel. By using this forward and backward mapping technique, forward interpolation can be implemented quickly and efficiently.
A 9 pixel-by-9 pixel working window slides over an input Bayer image. For each such window, a demosaicing operation is performed. For each such window, corrective processing is performed relative to that window to produce relative differences for that window. For each such window for which relative differences have been produced, those relative differences are regulated. For each window, a maximum is found for that window's regulated relative differences; in one embodiment of the invention, this maximum is used to select which channel is sharp. For each window, the colors in that window are corrected based on the relative difference-based maximum found for that window. For each window, edge oversharpening is softened in order to avoid artifacts in the output image. The result is an output image in which axial chromatic aberrations have been corrected.
H04N 5/232 - Devices for controlling television cameras, e.g. remote control
H04N 5/217 - Circuitry for suppressing or minimising disturbance, e.g. moire or halo in picture signal generation
H04N 9/64 - Circuits for processing colour signals
H04N 3/14 - Scanning details of television systemsCombination thereof with generation of supply voltages by means not exclusively optical-mechanical by means of electrically scanned solid-state devices
Techniques for detecting and addressing image flicker are disclosed. An imaging device that senses a distorted image and subsequently removes the distortion during processing can utilize an analysis module that obtains statistics indicative of image flicker prior to removing the distortion. An imaging device that features a diode for illuminating a field of view can utilize the diode as a photosensor to determine one or more flicker statistics to determine whether ambient lighting conditions are of the type that cause image flicker.
A measure of frame-to-frame rotation is determined. A global XY alignment of a pair of image frames is performed. At least one section of each of the X and Y integral projection vectors is determined, where aligned global vectors demonstrate a significant localized difference. Based on X and Y locations of the at least one section of the X and Y integral projection vectors, location, relative velocity and/or approximate area of at least one moving object within the sequence of image frames is/are determined.
H04N 7/18 - Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
G06K 9/46 - Extraction of features or characteristics of the image
G06K 9/66 - Methods or arrangements for recognition using electronic means using simultaneous comparisons or correlations of the image signals with a plurality of references, e.g. resistor matrix references adjustable by an adaptive method, e.g. learning
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/36 - Image preprocessing, i.e. processing the image information without deciding about the identity of the image
72.
Fast rotation estimation of objects in sequences of acquired digital images
A measure of frame-to-frame rotation is determined. A global XY alignment of a pair of frames is performed. Local XY alignments in at least two matching corner regions of the pair of images are determined after the global XY alignment. Based on differences between the local XY alignments, a global rotation is determined between the pair of frames.
H04N 7/18 - Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
G06K 9/46 - Extraction of features or characteristics of the image
G06K 9/66 - Methods or arrangements for recognition using electronic means using simultaneous comparisons or correlations of the image signals with a plurality of references, e.g. resistor matrix references adjustable by an adaptive method, e.g. learning
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/36 - Image preprocessing, i.e. processing the image information without deciding about the identity of the image
A measure of frame-to-frame rotation is determined. Integral projection vector gradients are determined and normalized for a pair of images. Locations of primary maximum and minimum peaks of the integral projection vector gradients are determined. Based on normalized distances between the primary maximum and minimum peaks, a global image rotation is determined.
A template matching module is configured to program a processor to apply multiple differently-tuned object detection classifier sets in parallel to a digital image to determine one or more of an object type, configuration, orientation, pose or illumination condition, and to dynamically switch between object detection templates to match a determined object type, configuration, orientation, pose, blur, exposure and/or directional illumination condition.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/46 - Extraction of features or characteristics of the image
G06K 9/68 - Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of reference, e.g. addressable memory
75.
Image sharpening via gradient environment detection
In an embodiment, a device comprises a plurality of elements, including logical elements, wherein the elements are configured to perform the operations of: in a neighborhood of pixels surrounding and including a particular pixel, applying a filter to multiple groups of pixels in the neighborhood to generate a set of filtered values; generating, based at least in part upon the set of filtered values, one or more sets of gradient values; based at least in part upon the one or more sets of gradient values, computing a first metric for an image environment in which the particular pixel is situated; determining a second metric for the image environment in which the particular pixel is situated, wherein the second metric distinguishes between a detail environment; and based at least in part upon the first metric and the second metric, computing a gradient improvement (GI) metric for the particular pixel.
G06K 9/48 - Extraction of features or characteristics of the image by coding the contour of the pattern
G06K 9/56 - Combinations of preprocessing functions using a local operator, i.e. means to operate on an elementary image point in terms of the immediate surroundings of this point
A method for detecting a redeye defect in a digital image containing an eye comprises converting the digital image into an intensity image, and segmenting the intensity image into segments each having a local intensity maximum. Separately, the original digital image is thresholded to identify regions of relatively high intensity and a size falling within a predetermined range. Of these, a region is selected having substantially the highest average intensity, and those segments from the segmentation of the intensity image whose maxima are located in the selected region are identified.
A technique is disclosed for calculating a value for a second color for a particular pixel. The technique selects a first set of neighboring pixels situated on a first side of the particular pixel, and a second set of neighboring pixels situated on an opposite side of the particular pixel. Based upon color values from the first set of neighboring pixels, the technique determines a first representative relationship, and based upon color values from the second set of neighboring pixels, the technique determines a second representative relationship. Based upon these representative relationships, the technique determines a target relationship between the value for the second color for the particular pixel and a value for a first color for the particular pixel. Based upon the target relationship and the value for the first color for the particular pixel, the technique calculates the value for the second color for the particular pixel.
An image processing technique includes acquiring a main image of a scene and determining one or more facial regions in the main image. The facial regions are analysed to determine if any of the facial regions includes a defect. A sequence of relatively low resolution images nominally of the same scene is also acquired. One or more sets of low resolution facial regions in the sequence of low resolution images are determined and analysed for defects. Defect free facial regions of a set are combined to provide a high quality defect free facial region. At least a portion of any defective facial regions of the main image are corrected with image information from a corresponding high quality defect free facial region.
An image acquisition device having a wide field of view includes a lens and image sensor configured to capture an original wide field of view (WFoV) image with a field of view of more than 90°. The device has an object detection engine that includes one or more cascades of object classifiers, e.g., face classifiers. A WFoV correction engine may apply rectilinear and/or cylindrical projections to pixels of the WFoV image, and/or non-linear, rectilinear and/or cylindrical lens elements or lens portions serve to prevent and/or correct distortion within the original WFoV image. One or more objects located within the original and/or distortion-corrected WFoV image is/are detectable by the object detection engine upon application of the one or more cascades of object classifiers.
An image acquisition sensor of a digital image acquisition apparatus is coupled to imaging optics for acquiring a sequence of images. Images acquired by the sensor are stored. A motion detector causes the sensor to cease capture of an image when the degree of movement in acquiring the image exceeds a threshold. A controller selectively transfers acquired images for storage. A motion extractor determines motion parameters of a selected, stored image. An image re-constructor corrects the selected image with associated motion parameters. A selected plurality of images nominally of the same scene are merged and corrected by the image re-constructor to produce a high quality image of the scene.
A method for detecting a redeye defect in a digital image containing an eye comprises converting the digital image into an intensity image, and segmenting the intensity image into segments each having a local intensity maximum. Separately, the original digital image is thresholded to identify regions of relatively high intensity and a size falling within a predetermined range. Of these, a region is selected having substantially the highest average intensity, and those segments from the segmentation of the intensity image whose maxima are located in the selected region are identified.
A digital image acquisition system includes a portable apparatus for capturing digital images and a digital processing component for detecting, analyzing, invoking subsequent image captures and informing the photographer regarding motion blur, and for reducing camera motion blur in an image captured by the apparatus. The digital processing component operates by comparing the image with at least one other image, for example a preview image, of nominally the same scene taken outside the exposure period of the main image. In one embodiment the digital processing component identifies at least one feature in a single preview image which is relatively less blurred than the corresponding feature in the main image, calculates a point spread function (PSF) in respect of such feature, and initiates a subsequent capture if determined that the motion blur exceeds a certain threshold. In another embodiment the digital processing determines the degree of blur by analyzing the motion blur in the captured image itself, and initiates a subsequent capture if determined that the motion blur exceeds a certain threshold. Such real time analysis may use the auto focusing mechanism to qualitatively determine the PSF.
A digital image acquisition system having no photographic film comprises an apparatus for capturing digital images and a flash unit for providing illumination during image capture. The system has a portrait mode for generating an image of a foreground object against a blurred background, the portrait mode being operable to capture first, second and third images (A, B and C) of nominally the same scene. One of the first and second images (A, B) is taken with flash and the other is taken without flash, and the third image (C) is blurred compared to the first and second images. The portrait mode is further operable to determine foreground and background regions of the scene using the first and second images (A, B), and to substitute the blurred background of the third image (C) for the background of an in-focus image of the scene. In one embodiment the in-focus image is one of the first and second images. In another embodiment the in-focus image is a fourth image.
An image capturing device (1) is disclosed comprising an electronic image detector (17) having a detecting surface (15), an optical projection system (5) for projecting an object within a field of view onto the detecting surface (15), and, optionally, a computing unit (19) for manipulating electronic information obtained from the image detector (17), wherein, the projection system (5) is adapted to project the object in a distorted way such that, when compared with a standard lens system, the projected image is expanded in a center region of the field of view and is compressed in a border region of the field of view. Preferably, the projection system (5) is adapted such that its point spread function in the border region of the field of view has a full width at half maximum corresponding essentially to the size of corresponding pixels of the image detector (17).
A method of processing an image includes traversing pixels of an image in a single pass over the image. An inverting function is applied to the pixels. A recursive filter is applied to the inverted pixel values. The filter has parameters which are derived from previously traversed pixel values of the image. A pixel value is combined with a filter parameter for the pixel to provide a processed pixel value for a processed image.
An image capturing device may include a detector including a plurality of sensing pixels, and an optical system adapted to project a distorted image of an object within a field of view onto the sensing pixels, wherein the optical system expands the image in a center of the field of view and compresses the image in a periphery of the field of view, wherein a first number of sensing pixels required to realize a maximal zoom magnification {circumflex over (Z)} at a minimum resolution of the image capturing device is less than a square of the maximal zoom magnification times a second number of sensing pixels required for the minimum resolution.
An imaging system includes an extended depth of field (EDOF) optical system, a sensor on a sensor substrate, and a securing mechanism adapted to secure the EDOF optical system directly to the sensor substrate.
A method for detecting a redeye defect in a digital image containing an eye comprises converting the digital image into an intensity image, and segmenting the intensity image into segments each having a local intensity maximum. Separately, the original digital image is thresholded to identify regions of relatively high intensity and a size falling within a predetermined range. Of these, a region is selected having substantially the highest average intensity, and those segments from the segmentation of the intensity image whose maxima are located in the selected region are identified.
A method of blurring an image includes acquiring two images of nominally a same scene taken at a different light exposure levels. At least one region of one of the images includes pixels having saturated intensity values. For at least one of the saturated pixels, values are extrapolated from the other image. At least a portion of a third image is blurred and re-scaled including pixels having the extrapolated values.
A technique involves distinguishing between foreground and background regions of a digital image of a scene. First and second images are captured of nominally a same scene. The first image is a relatively high resolution image taken with the foreground more in focus than the background, while the second image is a relatively low resolution reference image taken with the background more in focus than the foreground. Regions of the captured images are assigned as foreground or background. In accordance with the assigning, one or more processed images are rendered based on the first image or the second image, or both.
A digital image processing technique gathers visual meta data using a reference image. A main image and one or more reference images are captured on a hand-held or otherwise portable or spatial or temporal performance-based image capture device. The reference images are analyzed based on predefined criteria in comparison to the main image. Based on said analyzing, supplemental meta data are created and added to the main image at a digital data storage location.
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.
H04N 5/262 - Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
H04N 5/77 - Interface circuits between an apparatus for recording and another apparatus between a recording apparatus and a television camera
H04N 5/272 - Means for inserting a foreground image in a background image, i.e. inlay, outlay
H04N 5/232 - Devices for controlling television cameras, e.g. remote control
H04N 5/345 - Extracting pixel data from an image sensor by controlling scanning circuits, e.g. by modifying the number of pixels having been sampled or to be sampled by partially reading an SSIS array
G06K 9/32 - Aligning or centering of the image pick-up or image-field
H04N 9/804 - Transformation of the television signal for recording, e.g. modulation, frequency changingInverse transformation for playback involving pulse code modulation of the colour picture signal components
H04N 5/235 - Circuitry for compensating for variation in the brightness of the object
H04N 5/347 - Extracting pixel data from an image sensor by controlling scanning circuits, e.g. by modifying the number of pixels having been sampled or to be sampled by combining or binning pixels in SSIS
An estimated total camera motion between temporally proximate image frames is computed. A desired component of the estimated total camera motion is determined including distinguishing an undesired component of the estimated total camera motion, and including characterizing vector values of motion between the image frames. A counter is incremented for each pixel group having a summed luminance that is greater than a threshold. A counter may be decremented for pixels that are under a second threshold, or a zero bit may be applied to pixels below a single threshold. The threshold or thresholds is/are determined based on a dynamic luminance range of the sequence. The desired camera motion is computed including representing the vector values based on final values of counts for the image frames. A corrected image sequence is generated including the desired component of the estimated total camera motion, and excluding the undesired component.
An image processing technique includes acquiring a main image of a scene and determining one or more facial regions in the main image. The facial regions are analysed to determine if any of the facial regions includes a defect. A sequence of relatively low resolution images nominally of the same scene is also acquired. One or more sets of low resolution facial regions in the sequence of low resolution images are determined and analysed for defects. Defect free facial regions of a set are combined to provide a high quality defect free facial region. At least a portion of any defective facial regions of the main image are corrected with image information from a corresponding high quality defect free facial region.
A method and apparatus for efficiently performing digital signal processing is provided. In one embodiment, kernel matrix computations are simplified by grouping similar kernel coefficients together. Each coefficient group contains only coefficients having the same value. At least one of the coefficient groups has at least two coefficients. Techniques are disclosed herein to efficiently apply successive first order difference operations to a data signal. The techniques allow for a low gate count. In particular, the techniques allow for a reduction of the number of multipliers without increasing clock frequency, in an embodiment. The techniques update pixels of a data signal at a rate of two clock cycles per each pixel, in an embodiment. The techniques allow hardware that is used to process a first pixel to be re-used to start the processing of a second pixel while the first pixel is still being processed.
A face illumination normalization method includes acquiring a digital image including a face that appears to be illuminated unevenly. One or more uneven illumination classifier programs are applied to the face data to determine the presence of the face within the digital image and/or the uneven illumination condition of the face. The uneven illumination condition may be corrected to thereby generate a corrected face image appearing to have more uniform illumination, for example, to enhance face recognition.
G06K 9/68 - Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of reference, e.g. addressable memory
G06K 9/62 - Methods or arrangements for recognition using electronic means
Flash image orb artifacts arising from specular reflections from airborne particles are corrected. A specific location is detected within a digital image of a flash image airborne particle artifact (orb). A defined curved plane shape is electronically identified within the image. Luminances are analyzed of pixels within the identified shape to assess whether the shape in fact corresponds to an orb. The digital image is corrected by removing the orb. One or more pixel values are adjusted inside the orb, and one or more edge pixel values of the orb are also adjusted.
An unsatisfactory scene is disqualified as an image acquisition control for a camera. An image is acquired. One or more regions of facial or other key features are determined in the image. These regions are analyzed to determine whether they are unsatisfactorily blocked or shadowed, and if so, then the scene is disqualified as a candidate for a processed, permanent image while the feature continues to be blocked or shadowed.
A digital image acquisition device has an image acquisition sensor, a shutter, an aperture and optical elements for focusing an image on the sensor. The device includes a light source located in the body of the device. The light source is periodically activated with one of the aperture or shutter closed, and the device derives a map of defects on the surface of the sensor from a calibration image acquired by the sensor when illuminated by the light source.
A method of modifying the viewing parameters of digital images using face detection for achieving a desired spatial parameters based on one or more sub-groups of pixels that correspond to one or more facial features of the face. Such methods may be used for animating still images, automating and streamlining application such as the creation of slide shows and screen savers of images containing faces.
patents
