FULLY PARALLEL, LOW COMPLEXITY APPROACH TO SOLVING COMPUTER VISION PROBLEMS

    公开(公告)号:US20200160109A1

    公开(公告)日:2020-05-21

    申请号:US16749626

    申请日:2020-01-22

    Applicant: Google LLC

    Abstract: Values of pixels in an image are mapped to a binary space using a first function that preserves characteristics of values of the pixels. Labels are iteratively assigned to the pixels in the image in parallel based on a second function. The label assigned to each pixel is determined based on values of a set of nearest-neighbor pixels. The first function is trained to map values of pixels in a set of training images to the binary space and the second function is trained to assign labels to the pixels in the set of training images. Considering only the nearest neighbors in the inference scheme results in a computational complexity that is independent of the size of the solution space and produces sufficient approximations of the true distribution when the solution for each pixel is most likely found in a small subset of the set of potential solutions.

    HIERARCHICAL DISPARITY HYPOTHESIS GENERATION WITH SLANTED SUPPORT WINDOWS

    公开(公告)号:US20190287259A1

    公开(公告)日:2019-09-19

    申请号:US16158676

    申请日:2018-10-12

    Applicant: Google LLC

    Abstract: A method includes capturing a first image and a second image of a scene using at least one imaging camera of an imaging system. The first image and the second image form a stereo image pair and each comprises a plurality of pixels. Each of the plurality of pixels in the second image is initialized with a disparity hypothesis. Matching costs of the disparity hypothesis for each of the plurality of pixels in the second image are recursively determined, from an image tile of a smaller pixel size to an image tile of a larger pixel size, to generate an initial tiled disparity map including a plurality of image tiles. After refining the disparity value estimate of each image tile and including a slant hypothesis, a final disparity estimate for each pixel of the image is generated.

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