A system for modeling a roof structure comprising an aerial imagery database and a processor in communication with the aerial imagery database. The aerial imagery database stores a plurality of stereoscopic image pairs and the processor selects at least one stereoscopic image pair among the plurality of stereoscopic image pairs and related metadata from the aerial imagery database based on a geospatial region of interest. The processor identifies a target image and a reference image from the at least one stereoscopic pair and calculates a disparity value for each pixel of the identified target image to generate a disparity map. The processor generates a three dimensional point cloud based on the disparity map, the identified target image and the identified reference image, The processor optionally generates a texture map indicative of a three-dimensional representation of the roof structure based on the generated three dimensional point cloud.
A system for modeling a roof structure comprising an aerial imagery database and a processor in communication with the aerial imagery database. The aerial imagery database stores a plurality of stereoscopic image pairs and the processor selects at least one stereoscopic image pair among the plurality of stereoscopic image pairs and related metadata from the aerial imagery database based on a geospatial region of interest. The processor identifies a target image and a reference image from the at least one stereoscopic pair and calculates a disparity value for each pixel of the identified target image to generate a disparity map. The processor generates a three dimensional point cloud based on the disparity map, the identified target image and the identified reference image, The processor optionally generates a texture map indicative of a three-dimensional representation of the roof structure based on the generated three dimensional point cloud.
Systems and methods for generating augmented reality environments from 2D drawings are provided. The system performs a camera calibration process to determine how a camera transforms images from the real world into a 2D image plane. The system calculates a camera pose and determines an object position and an object orientation relative to a known coordinate system. The system detects and processes a 2D drawing/illustration and generates a 3D model from the 2D drawing/illustration. The system performs a rendering process, wherein the system generates an augmented reality environment which includes the 3D model superimposed on an image of the 2D drawing/illustration. The system can generate the augmented reality environment in real time, allowing the system to provide immediate feedback to the user. The images processed by the system can be from a video, from multiple image photography, etc.
Systems and methods for generating augmented reality environments from 2D drawings are provided. The system performs a camera calibration process to determine how a camera transforms images from the real world into a 2D image plane. The system calculates a camera pose and determines an object position and an object orientation relative to a known coordinate system. The system detects and processes a 2D drawing/illustration and generates a 3D model from the 2D drawing/illustration. The system performs a rendering process, wherein the system generates an augmented reality environment which includes the 3D model superimposed on an image of the 2D drawing/illustration. The system can generate the augmented reality environment in real time, allowing the system to provide immediate feedback to the user. The images processed by the system can be from a video, from multiple image photography, etc.
Computer vision systems and methods for detecting anomalous building models are provided. The systems and methods can detect anomalies in building models using one or more of an independent univariate Gaussian algorithm, a multivariate Gaussian algorithm, a combination of a multivariate Gaussian algorithm for continuous features and a frequency histogram algorithm for discrete features, and/or a bin frequency model. The system automatically processes computerized models to determine anomalies, and indicates whether the models are accurate and whether correction is required.
G06F 30/13 - Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
6.
COMPUTER VISION SYSTEMS AND METHODS FOR IDENTIFYING ANOMALIES IN BUILDING MODELS
Computer vision systems and methods for detecting anomalous building models are provided. The systems and methods can detect anomalies in building models using one or more of an independent univariate Gaussian algorithm, a multivariate Gaussian algorithm, a combination of a multivariate Gaussian algorithm for continuous features and a frequency histogram algorithm for discrete features, and/or a bin frequency model. The system automatically processes computerized models to determine anomalies, and indicates whether the models are accurate and whether correction is required.
A system for detecting and extracting a ground surface condition from an image comprising a memory and a processor in communication with the memory. The processor performs a high resolution scan of at least one input image and generates an orthomosaic model and a digital surface model based on the performed high resolution scan. The processor generates an image tile based on the generated models and determines a label indicative of a probability of a presence of a ground surface condition for each pixel of the generated image tile via a computer vision model. The processor generates a label tensor for the at least one input image based on the determined labels and extracts a two- dimensional geospatial representation of a detected ground surface condition based on the generated label tensor. The processor generates a report indicative of damage associated with the detected ground surface condition based on the extracted two-dimensional geospatial representation.
B60Q 9/00 - Arrangement or adaptation of signal devices not provided for in one of main groups
B60T 7/12 - Brake-action initiating means for automatic initiationBrake-action initiating means for initiation not subject to will of driver or passenger
B60T 8/171 - Detecting parameters used in the regulationMeasuring values used in the regulation
B60T 8/175 - Brake regulation specially adapted to prevent excessive wheel spin during vehicle acceleration, e.g. for traction control
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
A system and method for generating floor plans using a mobile device, comprising a memory and a processor in communication with the memory. The processor captures a plurality of walls in a room using one or more sensors of the mobile device. The processor then captures one or more openings in the room. The processor then generates a floor plan based on the walls and the openings.
A system for detecting and extracting a ground surface condition from an image comprising a memory and a processor in communication with the memory. The processor performs a high resolution scan of at least one input image and generates an orthomosaic model and a digital surface model based on the performed high resolution scan. The processor generates an image tile based on the generated models and determines a label indicative of a probability of a presence of a ground surface condition for each pixel of the generated image tile via a computer vision model. The processor generates a label tensor for the at least one input image based on the determined labels and extracts a two- dimensional geospatial representation of a detected ground surface condition based on the generated label tensor. The processor generates a report indicative of damage associated with the detected ground surface condition based on the extracted two-dimensional geospatial representation.
B60Q 9/00 - Arrangement or adaptation of signal devices not provided for in one of main groups
B60T 7/12 - Brake-action initiating means for automatic initiationBrake-action initiating means for initiation not subject to will of driver or passenger
B60T 8/171 - Detecting parameters used in the regulationMeasuring values used in the regulation
B60T 8/175 - Brake regulation specially adapted to prevent excessive wheel spin during vehicle acceleration, e.g. for traction control
10.
SYSTEM AND METHOD FOR GENERATING FLOOR PLANS USING USER DEVICE SENSORS
A system and method for generating floor plans using a mobile device, comprising a memory and a processor in communication with the memory. The processor captures a plurality of walls in a room using one or more sensors of the mobile device. The processor then captures one or more openings in the room. The processor then generates a floor plan based on the walls and the openings.
A system and method for generating models from digital images in an interactive environment comprising a memory and a processor in communication with the memory. The processor captures or derives metadata for one or more digital images. The processor derives transforms from the metadata to align the digital images with one or more three- dimensional ("3D") models of objects/structures represented in the digital image. The processor generates an interactive environment which allows a user to view a contextual model of each of the objects/structures in two dimensional ("2D") and 3D views.
A system and method for generating models from digital images in an interactive environment comprising a memory and a processor in communication with the memory. The processor captures or derives metadata for one or more digital images. The processor derives transforms from the metadata to align the digital images with one or more three- dimensional ("3D") models of objects/structures represented in the digital image. The processor generates an interactive environment which allows a user to view a contextual model of each of the objects/structures in two dimensional ("2D") and 3D views.
A system and method for automatically modeling symmetry planes and principal orientations from three dimensional ("3D") segments. The system comprises receiving a set of 3D segments representing a structure from the input source, wherein the set of 3D segments comprises one or more segment pairs. The system then generates symmetry plane data by calculating a symmetry plane for each of the one or more segment pairs. Next, the system accumulates the symmetry plane data in a Hough space. Lastly, the system constructs one or more Hough space symmetry planes from the symmetry plane data and calculates a principal orientation of the structure.
14.
COMPUTER VISION SYSTEMS AND METHODS FOR MODELING THREE DIMENSIONAL STRUCTURES USING TWO-DIMENSIONAL SEGMENTS DETECTED IN DIGITAL AERIAL IMAGES
A system for modeling a three-dimensional structure utilizing two-dimensional segments comprising a memory and a processor in communication with the memory. The processor extracts a plurality of two-dimensional segments corresponding to the three- dimensional structure from a plurality of images indicative of different views of the three- dimensional structure. The processor determines a plurality of three-dimensional candidate segments based on the extracted plurality of two-dimensional segments and adds the plurality of three-dimensional candidate segments to a three- dimensional segment cloud. The processor transforms the three-dimensional segment cloud into a wireframe indicative of the three-dimensional structure by performing a wireframe extraction process on the three-dimensional segment cloud.
15.
COMPUTER VISION SYSTEMS AND METHODS FOR AUTOMATICALLY DETECTING, CLASSIFING, AND PRICING OBJECTS CAPTURED IN IMAGES OR VIDEOS
A system and method for automatically detecting, classifying, and processing objects captured in an image. The system receives an image from the image source and detects one or more objects in the image. The system then performs a high-level classification of each of the one or more objects in the image and extracts each of the one or more objects from the image. The system then performs a specific classification of each of the one or more objects and determines a price of each of the one or more objects. Finally, the system generates a pricing report comprising a price of each of the one or more objects.
A system and method for automatically detecting, classifying, and processing objects captured in an image. The system receives an image from the image source and detects one or more objects in the image. The system then performs a high-level classification of each of the one or more objects in the image and extracts each of the one or more objects from the image. The system then performs a specific classification of each of the one or more objects and determines a price of each of the one or more objects. Finally, the system generates a pricing report comprising a price of each of the one or more objects.
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
A system for modeling a three-dimensional structure utilizing two-dimensional segments comprising a memory and a processor in communication with the memory. The processor extracts a plurality of two-dimensional segments corresponding to the three- dimensional structure from a plurality of images indicative of different views of the three- dimensional structure. The processor determines a plurality of three-dimensional candidate segments based on the extracted plurality of two-dimensional segments and adds the plurality of three-dimensional candidate segments to a three-dimensional segment cloud. The processor transforms the three-dimensional segment cloud into a wireframe indicative of the three-dimensional structure by performing a wireframe extraction process on the three-dimensional segment cloud.
A system and method for automatically modeling symmetry planes and principal orientations from three dimensional ("3D") segments. The system comprises receiving a set of 3D segments representing a structure from the input source, wherein the set of 3D segments comprises one or more segment pairs. The system then generates symmetry plane data by calculating a symmetry plane for each of the one or more segment pairs. Next, the system accumulates the symmetry plane data in a Hough space. Lastly, the system constructs one or more Hough space symmetry planes from the symmetry plane data and calculates a principal orientation of the structure.
A system and method for generating a parametric model of a roof structure comprising a processor in communication with a memory. The system receives a plurality of parameters of each roof component composing the roof stmcture and performs a geometry creation based on the received plurality of parameters. The system generates a constrained three-dimensional geometry based on an output of the geometry creation, and displays a three-dimensional model of the roof structure based on the constrained three- dimensional geometry.
A system for modeling a roof of a structure comprising a first database, a second database and a processor in communication with the first database and the second database. The processor selects one or more images and the respective metadata thereof from the first database based on a received a geospatial region of interest. The processor generates two-dimensional line segment geometries in pixel space based on two-dimensional outputs generated by a neural network in pixel space of at least one roof stmcture present in the selected one or more images. The processor classifies the generated two-dimensional line segment geometries into at least one contour graph based on three-dimensional data received from the second database and generates a three-dimensional representation of the at least one roof structure based on the at least one contour graph and the received three- dimensional data.
A system and method for generating a parametric model of a roof structure comprising a processor in communication with a memory. The system receives a plurality of parameters of each roof component composing the roof stmcture and performs a geometry creation based on the received plurality of parameters. The system generates a constrained three-dimensional geometry based on an output of the geometry creation, and displays a three-dimensional model of the roof structure based on the constrained three- dimensional geometry.
A system for modeling a roof of a structure comprising a first database, a second database and a processor in communication with the first database and the second database. The processor selects one or more images and the respective metadata thereof from the first database based on a received a geospatial region of interest. The processor generates two-dimensional line segment geometries in pixel space based on two-dimensional outputs generated by a neural network in pixel space of at least one roof stmcture present in the selected one or more images. The processor classifies the generated two-dimensional line segment geometries into at least one contour graph based on three-dimensional data received from the second database and generates a three-dimensional representation of the at least one roof structure based on the at least one contour graph and the received three- dimensional data.
G06T 17/10 - Volume description, e.g. cylinders, cubes or using CSG [Constructive Solid Geometry]
G06T 19/20 - Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
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
A system and method for lean ortho correction for computer models of structures. The system displays an image of a structure on a user interface and projects a structure model onto the image. Next, the system identifies a first world three-dimensional ("3D") point in the image, a second world 3D point in the image, and a third world 3ID point in the image, The system then transforms coordinates of the structure model using the first world 3D point, the second world 3D point, the third world 3D point, and a lean ortho correction algorithm.
Systems and methods for aligning digital image datasets to a computer model of a structure. The system receives a plurality of reference images from an input image dataset and identifies common ground control points ("GCPs") in the reference images. The system then calculates virtual three-dimensional ("3D") coordinates of the measured GCPs. Next, the system calculates and projects two-dimensional ("2D") image coordinates of the virtual 3D coordinates into all of the images. Finally, using the projected 2D image coordinates, the system performs spatial resection of all of the images in order to rapidly align all of the images.
Systems and methods for aligning digital image datasets to a computer model of a structure. The system receives a plurality of reference images from an input image dataset and identifies common ground control points ("GCPs") in the reference images. The system then calculates virtual three-dimensional ("3D") coordinates of the measured GCPs. Next, the system calculates and projects two-dimensional ("2D") image coordinates of the virtual 3D coordinates into all of the images. Finally, using the projected 2D image coordinates, the system performs spatial resection of all of the images in order to rapidly align all of the images.
Systems and methods for property feature detection and extraction using digital images. The image sources could include aerial imagery, satellite imagery, ground-based imagery, imagery taken from unmanned aerial vehicles (UAVs), mobile device imagery, etc. The detected geometric property features could include tree canopy, pools and other bodies of water, concrete flatwork, landscaping classifications (gravel, grass, concrete, asphalt, etc.), trampolines, property structural features (structures, buildings, pergolas, gazebos, terraces, retaining walls, and fences), and sports courts. The system can automatically extract these features from images and can then project them into world coordinates relative to a known surface in world coordinates (e.g., from a digital terrain model).
Systems and methods for property feature detection and extraction using digital images. The image sources could include aerial imagery, satellite imagery, ground-based imagery, imagery taken from unmanned aerial vehicles (UAVs), mobile device imagery, etc. The detected geometric property features could include tree canopy, pools and other bodies of water, concrete flatwork, landscaping classifications (gravel, grass, concrete, asphalt, etc.), trampolines, property structural features (structures, buildings, pergolas, gazebos, terraces, retaining walls, and fences), and sports courts. The system can automatically extract these features from images and can then project them into world coordinates relative to a known surface in world coordinates (e.g., from a digital terrain model).
A system and method for mission planning, flight automation, and capturing of high-resolution images by unmanned aircraft is provided. The system includes at least one hardware processor including a controller configured to generate and execute a flight plan that automatically detects and avoids obstacles present in a flight path for capturing the high-resolution images, requiring no (or, minimal) user involvement. The system can also predict obstacles in flight paths, and automatically calculate a flight path that avoids predicted obstacles.
Systems and methods for rapidly developing annotated computer models of structures and properties is provided. The system generates three-dimensional (3D) models of structures and property using a wide variety of digital imagery, and/or can process existing 3D models created by other systems. The system processes the 3D models to automatically identify candidate objects within the 3D models that may be suitable for annotation, such as roof faces, chimneys, windows, gutters, etc., using computer vision techniques to automatically identify such objects. Once the candidate objects have been identified, the system automatically generates user interface screens which gather relevant information related to the candidate objects, so as to rapidly obtain, associate, and store annotation information related to the candidate objects. When all relevant annotation information has been gathered and associated with model objects, the system can create a list of materials that can be used for future purposes, such as repair and/or reconstruction of real- world structures and property.
Systems and methods for rapidly developing annotated computer models of structures and properties is provided. The system generates three-dimensional (3D) models of structures and property using a wide variety of digital imagery, and/or can process existing 3D models created by other systems. The system processes the 3D models to automatically identify candidate objects within the 3D models that may be suitable for annotation, such as roof faces, chimneys, windows, gutters, etc., using computer vision techniques to automatically identify such objects. Once the candidate objects have been identified, the system automatically generates user interface screens which gather relevant information related to the candidate objects, so as to rapidly obtain, associate, and store annotation information related to the candidate objects. When all relevant annotation information has been gathered and associated with model objects, the system can create a list of materials that can be used for future purposes, such as repair and/or reconstruction of real- world structures and property.
A system and method for mission planning, flight automation, and capturing of high-resolution images by unmanned aircraft is provided. The system includes at least one hardware processor including a controller configured to generate and execute a flight plan that automatically detects and avoids obstacles present in a flight path for capturing the high-resolution images, requiring no (or, minimal) user involvement. The system can also predict obstacles in flight paths, and automatically calculate a flight path that avoids predicted obstacles.
A system and method for mission planning and flight automation for an unmanned aircraft comprising generating an aerial imagery map of a capture area; generating a flight plan based on criteria for capturing images used to create a model of a feature present in the images; comparing the generated aerial imagery map with the generated flight plan; determining whether there is a possible collision between an obstacle associated with the generated aerial imagery map and the unmanned aircraft along a flight path of the generated flight plan; and executing, based on the determination, the generated flight plan.
A system and method for mission planning and flight automation for an unmanned aircraft comprising generating an aerial imagery map of a capture area; generating a flight plan based on criteria for capturing images used to create a model of a feature present in the images; comparing the generated aerial imagery map with the generated flight plan; determining whether there is a possible collision between an obstacle associated with the generated aerial imagery map and the unmanned aircraft along a flight path of the generated flight plan; and executing, based on the determination, the generated flight plan.
Described in detail herein are systems and methods for generating computerized models of structures using geometry extraction and reconstruction techniques. The system includes a computing device coupled to a input device. The input device obtains raw data scanned by a sensor. The computing device is programmed to execute a data fusion process is applied to fuse the raw data, and a geometry extraction process is performed on the fused data to extract features such as walls, floors, ceilings, roof planes, etc. Large- and small-scale features of the structure are reconstructed using the extracted features. The large- and small-scale features are reconstructed by the system into a floor plan (contour) and/or a polyhedron corresponding to the structure. The system can also process exterior features of the structure to automatically identify condition and areas of roof damage.
Described in detail herein are systems and methods for generating computerized models of structures using geometry extraction and reconstruction techniques. The system includes a computing device coupled to a input device. The input device obtains raw data scanned by a sensor. The computing device is programmed to execute a data fusion process is applied to fuse the raw data, and a geometry extraction process is performed on the fused data to extract features such as walls, floors, ceilings, roof planes, etc. Large- and small-scale features of the structure are reconstructed using the extracted features. The large- and small-scale features are reconstructed by the system into a floor plan (contour) and/or a polyhedron corresponding to the structure. The system can also process exterior features of the structure to automatically identify condition and areas of roof damage.
patents
