Intel Corporation

Maciej Adam Kaminski

Amit Aneja

Dhawal Srivastava

Takeshi Kevin Yamane Musgrave

Wei-Yu Tsai

Jayaram Puttaswamy

Robert Mahieu

Mithali Shivkumar

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.

Parallelism in disparity map generation

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.

Distributed object detection processing

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Chandler, AZ, United States of America

Maciej Adam Kaminski