Patent classifications
G06T7/596
DIGITAL IMAGE SUB-DIVISION
A digital image processing method performed by a computer is disclosed. A digital image captured by a real camera having intrinsic and extrinsic parameters is received. The intrinsic parameters include a native principal point defined relative to an origin of a coordinate system of the digital image. The digital image is sub-divided into a plurality of sub-images. For each sub-image of the plurality of sub-images, the sub-image is associated with a synthesized recapture camera having synthesized intrinsic and extrinsic parameters mapped from the real camera. The synthesized intrinsic parameters include the native principal point defined relative to an origin of a coordinate system of the sub-image.
Apparatus and methods for determining multi-subject performance metrics in a three-dimensional space
Apparatus and methods for extraction and calculation of multi-person performance metrics in a three-dimensional space. An example apparatus includes a detector to identify a first subject in a first image captured by a first image capture device based on a first set of two-dimensional kinematic keypoints in the first image, the two-dimensional kinematic keypoints corresponding to a joint of the first subject, the first image capture device associated with a first view of the first subject, a multi-view associator to verify the first subject using the first image and a second image captured by a second image capture device, the second image capture device associated with a second view of the first subject, the second view different than the first view, and a keypoint generator to generate three-dimensional keypoints for the first subject using the first set of two-dimensional kinematic keypoints.
SYSTEM AND METHOD FOR DETERMINING OPERATING DEFLECTION SHAPES OF A STRUCTURE USING OPTICAL TECHNIQUES
A system for measuring total operating deflection shapes of a structure includes one or more imagers, each including two cameras spaced apart from one another and each oriented and positioned to have corresponding fields of view of a different corresponding section of the structure, with the corresponding sections that may include overlap area of the structure within each of the different sections of the structure. Each of the cameras generates a corresponding data stream, which is communicated to a controller, which is configured to measure the response of the structure to an excitation, such as a vibration or an impulse. The system is configured to convert time-domain data from each of the data streams to the frequency-domain data using a Fourier Transform algorithm and stitching the shapes to obtain the total operating deflection shapes of the structure by scaling and stitching together the frequency-domain data.
Method for 3D reconstruction of an object
The invention relates to a method for 3D reconstruction of an object comprising the following steps: generating a plurality of images of an object by at least one camera; extracting features of the object from the plurality of images; generating a cloud of three dimensional points arranged in a three dimensional model representing the object; identifying the images each of which comprises at least one of a subset of said features; determining a first set of three dimensional points corresponding to the subset of said features and a second set of three dimensional points; determining a mathematical equation which corresponds to a predefined three dimensional geometric structure as a building block of the object by means of the first set and the second set of the three dimensional points; and rendering a three dimensional model of the object by means of at least the predefined three dimensional geometric structure.
System and Method for Performing Quality Control of Manufactured Models
Disclosed herein are example embodiments of methods and systems for identifying manufacturing defects of a manufactured dentition model. One of the methods for performing quality control comprises: determining whether the manufactured dentition model is a good or a defective product based on a statistical characteristic of a differences model. The differences model can be generated based on differences between a scanned 3D patient-dentition data and a scanned 3D manufactured-dentition data. The scanned 3D patient-dentition data can be generated using 3D data of a patient's dentition, and the scanned 3D manufactured-dentition data can be generated using 3D data of the manufactured dentition model. The manufactured dentition model can be a 3D printed model.
3D representation reconstruction from images using volumic probability data
To generate 3D representation of a scene volume, the present invention combines the 3D skeleton approach and the shape from silhouette approach. The present invention efficiently works on complex scenes like sport events with multiple players in a stadium, with an ability to detect a wide number of interoperating 3D objects like multiple players.
System and method for 3D profile determination using model-based peak selection
This invention provides a system and method for selecting the correct profile from a range of peaks generated by analyzing a surface with multiple exposure levels applied at discrete intervals. The cloud of peak information is resolved by comparison to a model profile into a best candidate to represent an accurate representation of the object profile. Illustratively, a displacement sensor projects a line of illumination on the surface and receives reflected light at a sensor assembly at a set exposure level. A processor varies the exposure level setting in a plurality of discrete increments, and stores an image of the reflected light for each of the increments. A determination process combines the stored images and aligns the combined images with respect to a model image. Points from the combined images are selected based upon closeness to the model image to provide a candidate profile of the surface.
ACCELERATION METHOD OF DEPTH ESTIMATION FOR MULTIBAND STEREO CAMERAS
The present invention belongs to the field of image processing and computer vision, and discloses an acceleration method of depth estimation for multiband stereo cameras. In the process of depth estimation, during binocular stereo matching in each band, through compression of matched images, on one hand, disparity equipotential errors caused by binocular image correction can be offset to make the matching more accurate, and on the other hand, calculation overhead is reduced. In addition, before cost aggregation, cost diagrams are transversely compressed and sparsely matched, thereby reducing the calculation overhead again. Disparity diagrams obtained under different modes are fused to obtain all-weather, more complete and more accurate depth information.
System and method for determining operating deflection shapes of a structure using optical techniques
A system for measuring total operating deflection shapes of a structure includes one or more imagers, each including two cameras spaced apart from one another and each oriented and positioned to have corresponding fields of view of a different corresponding section of the structure, with the corresponding sections that may include overlap area of the structure within each of the different sections of the structure. Each of the cameras generates a corresponding data stream, which is communicated to a controller, which is configured to measure the response of the structure to an excitation, such as a vibration or an impulse. The system is configured to convert time-domain data from each of the data streams to the frequency-domain data using a Fourier Transform algorithm and stitching the shapes to obtain the total operating deflection shapes of the structure by scaling and stitching together the frequency-domain data.
Depth extraction
A computer-implemented method of training a depth uncertainty estimator comprises receiving, at a training computer system, a set of training examples, each training example comprising (i) a stereo image pair and (ii) an estimated disparity map computed from at least one image of the stereo image pair by a depth estimator. The training computer system executes a training process to learn one or more uncertainty estimation parameters of a perturbation function, the uncertainty estimation parameters for estimating uncertainty in disparity maps computed by the depth estimator. The training process is performed by sampling a likelihood function based on the training examples and the perturbation function, thereby obtaining a set of sampled values for learning the one or more uncertainty estimation parameters. The likelihood function measures similarity between one image of each training example and a reconstructed image computed by transforming the other image of that training example based on a possible true disparity map derived from the estimated disparity map of that training example and the perturbation function.