Patents by Inventor Maruthi Sandeep Maddipatla

Maruthi Sandeep Maddipatla has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Point cloud viewpoint and scalable compression/decompression
    Patent number: 11049266
    Abstract: An apparatus comprises a processor to divide a first point cloud data set frame representing a three dimensional space at a first point in time into a matrix of blocks, determine at least one three dimensional (3D) motion vector for at least a subset of blocks in the matrix of blocks, generate a predicted second point cloud data set frame representing a prediction of the three dimensional space at a second point in time by applying the at least one 3D motion vector to the subset of blocks in the matrix of blocks, compare the predicted second point cloud data set frame to a second point cloud data set frame representing a prediction of the three dimensional space at a second point in time to generate a prediction error parameter, and encode the second point cloud data set frame as a function of the first point cloud data set frame and the at least one three dimensional (3D) motion vector when the prediction error factor is beneath an error threshold to produce an encoded second point cloud data set frame.
    Type: Grant
    Filed: July 31, 2018
    Date of Patent: June 29, 2021
    Assignee: INTEL CORPORATION
    Inventors: Scott Janus, Barnan Das, Hugues Labbe, Jong Dae Oh, Gokcen Cilingir, James Holland, Narayan Biswal, Yi-Jen Chiu, Qian Xu, Mayuresh Varerkar, Sang-Hee Lee, Stanley Baran, Srikanth Potluri, Jason Ross, Maruthi Sandeep Maddipatla
  • POINT CLOUD VIEWPOINT AND SCALABLE COMPRESSION/DECOMPRESSION
    Publication number: 20200043182
    Abstract: Embodiments described herein provide an apparatus comprising a processor to divide a first point cloud data set frame representing a three dimensional space at a first point in time into a matrix of blocks, determine at least one three dimensional (3D) motion vector for at least a subset of blocks in the matrix of blocks, generate a predicted second point cloud data set frame representing a prediction of the three dimensional space at a second point in time by applying the at least one 3D motion vector to the subset of blocks in the matrix of blocks, compare the predicted second point cloud data set frame to a second point cloud data set frame representing a prediction of the three dimensional space at a second point in time to generate a prediction error parameter, and encode the second point cloud data set frame as a function of the first point cloud data set frame and the at least one three dimensional (3D) motion vector when the prediction error factor is beneath an error threshold to produce an encoded s
    Type: Application
    Filed: July 31, 2018
    Publication date: February 6, 2020
    Applicant: Intel Corporation
    Inventors: Scott Janus, Barnan Das, Hugues Labbe, Jong Dae Oh, Gokcen Cilingir, James Holland, Narayan Biswal, Yi-Jen Chiu, Qian Xu, Mayuresh Varerkar, Sang-Hee Lee, Stanley Baran, Srikanth Potluri, Jason Ross, Maruthi Sandeep Maddipatla