US 12,169,953 B2
Predictive tree-based geometry coding for a point cloud
Wen Gao, Palo Alto, CA (US); Xiang Zhang, Palo Alto, CA (US); and Shan Liu, Palo Alto, CA (US)
Assigned to TENCENT AMERICA LLC, Palo Alto, CA (US)
Filed by TENCENT AMERICA LLC, Palo Alto, CA (US)
Filed on Feb. 5, 2024, as Appl. No. 18/432,973.
Application 18/432,973 is a continuation of application No. 17/324,627, filed on May 19, 2021, granted, now 11,941,856.
Claims priority of provisional application 63/067,286, filed on Aug. 18, 2020.
Prior Publication US 2024/0177356 A1, May 30, 2024
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 encoding point cloud data, executable by a processor, comprising:
receiving data corresponding to a point cloud;
determining 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 decode 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
encoding the received data corresponding to the point cloud based on the reduced number of contexts.