The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jun. 29, 2021
Filed:
Jul. 31, 2018
Intel Corporation, Santa Clara, CA (US);
Scott Janus, Loomis, CA (US);
Barnan Das, Newark, CA (US);
Hugues Labbe, Granite Bay, CA (US);
Jong Dae Oh, San Jose, CA (US);
Gokcen Cilingir, San Jose, CA (US);
James Holland, Folsom, CA (US);
Narayan Biswal, Folsom, CA (US);
Yi-Jen Chiu, San Jose, CA (US);
Qian Xu, Folsom, CA (US);
Mayuresh Varerkar, Folsom, CA (US);
Sang-Hee Lee, San Jose, CA (US);
Stanley Baran, Chandler, AZ (US);
Srikanth Potluri, Folsom, CA (US);
Jason Ross, Folsom, CA (US);
Maruthi Sandeep Maddipatla, Sacramento, CA (US);
INTEL CORPORATION, Santa Clara, CA (US);
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.