A system for single photon avalanche diode image capture is configurable to, over a frame capture time period, selectively activate an illuminator to alternately emit light from the illuminator and refrain from emitting light from the illuminator. The system is configurable to, over the frame capture time period, perform a plurality of sequential shutter operations to configure each SPAD pixel of the SPAD array to enable photon detection. The plurality of sequential shutter operations generates, for each SPAD pixel of the SPAD array, a plurality of binary counts indicating whether a photon was detected during each of the plurality of sequential shutter operations. The system is configurable to, based on a first set of binary counts of the plurality of binary counts, generate an ambient light image. The system is configurable to, based on a second set of binary counts of the plurality of binary counts, generate an illuminated image.

A system and a method are disclosed for a structured-light system to estimate depth in an image. An image is received in which the image is of a scene onto which a reference light pattern has been projected. The projection of the reference light pattern includes a predetermined number of particular sub-patterns. A patch of the received image and a sub-pattern of the reference light pattern are matched based on either a hardcode template matching technique or a probability that the patch corresponds to the sub-pattern. If a lookup table is used, the table may be a probability matrix, may contain precomputed correlations scores or may contain precomputed class IDs. An estimate of depth of the patch is determined based on a disparity between the patch and the sub-pattern.

A system and a method are disclosed for a structured-light system to estimate depth in an image. An image is received in which the image is of a scene onto which a reference light pattern has been projected. The projection of the reference light pattern includes a predetermined number of particular sub-patterns. A patch of the received image and a sub-pattern of the reference light pattern are matched based on either a hardcode template matching technique or a probability that the patch corresponds to the sub-pattern. If a lookup table is used, the table may be a probability matrix, may contain precomputed correlations scores or may contain precomputed class IDs. An estimate of depth of the patch is determined based on a disparity between the patch and the sub-pattern.

An HMD (head-mounted display) device is disclosed. The HMD device is communicatively connected to a tracking device. The HMD device includes a host memory and a host processor. The host memory is configured to store a host map. The host processor is configured to obtain a client capability data from the tracking device, to generate a partial map from the host map according to the client capability data, and to send the partial map to the tracking device.

An HMD (head-mounted display) device is disclosed. The HMD device is communicatively connected to a tracking device. The HMD device includes a host memory and a host processor. The host memory is configured to store a host map. The host processor is configured to obtain a client capability data from the tracking device, to generate a partial map from the host map according to the client capability data, and to send the partial map to the tracking device.

Methods, systems, devices and computer software/program code products enable efficiently finding stereo correspondence between a feature or set of features in a first image or signal, and a search domain in a second image or signal.

In a computer-implemented method and system for capturing the condition of a structure, the structure is scanned with an unmanned aerial vehicle (UAV). Data collected by the UAV corresponding to points on a surface of a structure is received and a 3D point cloud is generated for the structure, where the 3D point cloud is generated based at least in part on the received UAV data. A 3D model of the surface of the structure is reconstructed using the 3D point cloud.

In a computer-implemented method and system for capturing the condition of a structure, the structure is scanned with an unmanned aerial vehicle (UAV). Data collected by the UAV corresponding to points on a surface of a structure is received and a 3D point cloud is generated for the structure, where the 3D point cloud is generated based at least in part on the received UAV data. A 3D model of the surface of the structure is reconstructed using the 3D point cloud.

An imagery processing system determines pixel color values for pixels of captured imagery from volumetric data, providing alternative pixel color values. A main imagery capture device, such as a camera, captures main imagery such as still images and/or video sequences, of a live action scene. Alternative devices capture imagery of the live action scene, in some spectra and form, and capture information related to pixel color values for multiple depths of a scene, which can be processed to provide reconstruction.

ADAS includes a processing circuit and a memory which stores instructions executable by the processing circuit. The processing circuit executes the instructions to cause the ADAS to receive, from a vehicle that is in motion, a video sequence, generate a position image including at least one object included in the stereo image, generate a second position information associated with the at least one object based on reflected signals received from the vehicle, determine regions each including at least a portion of the at least one object as candidate bounding boxes based on the stereo image and the position image, and selectively adjusting class scores of respective ones of the candidate bounding boxes associated with the at least one object based on whether a respective first position information of the respective ones of the candidate bounding boxes matches the second position information.