HIERARCHICAL ENTROPY ENCODING AND DECODING

Patent №

US 9,035,807

Granted

2015-05-19

Filed 2014

Owner

THOMSON LICENSING

Lab

AI components

1

vision

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

14240066

A particular implementation receives geometry data of a 3D mesh, and represents the geometry data with an octree. The particular implementation partitions the octree into three parts, wherein the symbols corresponding to the middle part of the octree are hierarchical entropy encoded. To partition the octree into three parts, different thresholds are used. Depending on whether a symbol associated with a node is an S1 symbol, the child node of the node is included in the middle part or the upper part of the octree. In hierarchical entropy encoding, a non-S1 symbol is first encoded as a pre-determined symbol ‘X’ using symbol set S2={S1, ‘X’} and the non-S1 symbol itself is then encoded using symbol set S0 (S2⊂S0), and an S1 symbol is encoded using symbol set S2. Another implementation defines corresponding hierarchical entropy decoding. A further implementation reconstructs the octree and restores the geometry data of a 3D mesh from the octree representation.

VisionH03M 7/00G06T 9/001G06T 9/40G06T 17/005H04N 19/96

AI classification

Vision0.98
Knowledge representation0.49
Machine learning0.08
Evolutionary computation0.00
AI hardware0.00
Speech0.00
Natural language0.00
Planning0.00

Ownership

THOMSON LICENSING

assignment · 329230405

Assignors

JIANG, WENFEI, CAI, KANGYING, HU, PING

On an employer assignment, the assignors are typically the inventors.

From the same owner

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