US 11,941,856 B2
Predictive tree-based geometry coding for a point cloud
Wen Gao, West Windsor, NJ (US); Xiang Zhang, Mountain View, CA (US); and Shan Liu, San Jose, CA (US)
Assigned to TENCENT AMERICA LLC, Palo Alto, CA (US)
Filed by TENCENT AMERICA LLC, Palo Alto, CA (US)
Filed on May 19, 2021, as Appl. No. 17/324,627.
Claims priority of provisional application 63/067,286, filed on Aug. 18, 2020.
Prior Publication US 2022/0058837 A1, Feb. 24, 2022
Int. Cl. G06T 9/40 (2006.01); G06T 9/00 (2006.01); G06T 17/20 (2006.01)
CPC G06T 9/40 (2013.01) [G06T 9/001 (2013.01); G06T 17/205 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method of decoding point cloud data, executable by a processor, comprising:
receiving data corresponding to a point cloud;
reducing a number of contexts associated with the received data based on reducing a size of a context array corresponding to syntax elements for predictive tree-based coding of the point cloud, wherein the context array is a three-dimensional array that indicates a total number of contexts required to encode the syntax elements associated with the received data, wherein the reducing comprises reducing a size of at least one dimension of the context array from a first value to a second value less than the first value; and
decoding the received data corresponding to the point cloud based on the reduced number of contexts.