Abstract: Input images are partitioned into non-overlapping segments perpendicular to a disparity dimension of the input images. Each segment includes a contiguous region of pixels spanning from a first edge to a second edge of the image, with the two edges parallel to the disparity dimension. In some aspects, contiguous input image segments are assigned in a “round robin” manner to a set of sub-images. Each pair of input images generates a corresponding pair of sub-image sets. Semi-global matching processes are then performed on pairs of corresponding sub-images generated from each input image. The SGM processes may be run in parallel, reducing an elapsed time to generate respective disparity sub-maps. The disparity sub-maps are then combined to provide a single disparity map of equivalent size to the original two input images.

Abstract: Various systems and methods for implementing distributed object detection processing are described herein. An object detection system includes a plurality of computer vision accelerators to process a respective plurality of portions of an input image and produce a list of detected objects in the respective plurality of portions of the input image; and a processor subsystem to: combine the list of detected objects from each of the plurality of computer vision accelerators, to produce a combined list of detected objects; sort the combined list of detected objects; and remove duplicate entries in the combined list of detected objects to produce an output list of detected objects.

Abstract: Input images are partitioned into non-overlapping segments perpendicular to a disparity dimension of the input images. Each segment includes a contiguous region of pixels spanning from a first edge to a second edge of the image, with the two edges parallel to the disparity dimension. In some aspects, contiguous input image segments are assigned in a “round robin” manner to a set of sub-images. Each pair of input images generates a corresponding pair of sub-image sets. Semi-global matching processes are then performed on pairs of corresponding sub-images generated from each input image. The SGM processes may be run in parallel, reducing an elapsed time to generate respective disparity sub-maps. The disparity sub-maps are then combined to provide a single disparity map of equivalent size to the original two input images.

Abstract: Various systems and methods for implementing distributed object detection processing are described herein. An object detection system includes a plurality of computer vision accelerators to process a respective plurality of portions of an input image and produce a list of detected objects in the respective plurality of portions of the input image; and a processor subsystem to: combine the list of detected objects from each of the plurality of computer vision accelerators, to produce a combined list of detected objects; sort the combined list of detected objects; and remove duplicate entries in the combined list of detected objects to produce an output list of detected objects.