Point Cloud Encoder Planar Mode Flag Merging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current point cloud compression methods, particularly Geometry-based Point Cloud Compression (GPCC), are inefficient in sparse point clouds due to excessive bit usage in planar mode encoding, as they encode individual flags for each direction even when the node is eligible for planar mode in multiple directions.
Innovation Solution
The method determines eligibility for planar mode in at least two directions and uses a single planar flag to indicate planar context information, reducing the number of bits needed for encoding and decoding by combining context information across directions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If individual planar flags are encoded for each direction, then planar mode encoding is applied to eligible nodes, but the number of bits required increases excessively for sparse point clouds
Solution Approach 1:
The patent merges multiple planar flags into a single unified planar flag that indicates planar context information for multiple directions simultaneously. This combining approach reduces the number of bits from encoding individual directional flags to encoding a single shared flag, directly addressing the contradiction between maintaining encoding precision and reducing bit quantity.
Solution Approach 2:
The single planar flag serves multiple functions by indicating planar context information across different directions (e.g., XY plane, XZ plane, YZ plane) rather than requiring separate flags for each direction. This multi-functionality allows the same flag to replace multiple directional indicators, reducing bit usage while preserving encoding accuracy for sparse point clouds.
2Reliability
If planar mode is encoded for all three directions independently, then comprehensive planar context is captured, but device complexity increases
Solution Approach 1:
The patent combines multiple planar mode indicators into a single planar flag structure that can represent planar context across different directions. This merging reduces the complexity of the encoding system by eliminating redundant flag handling logic while maintaining the ability to accurately represent planar geometries through the unified flag's contextual information.
Data Source
AI summary
A method for encoding a point cloud to generate a bitstream of compressed point cloud data is provided, wherein the point cloud's geometry is represented by an octree-based structure with a plurality of nodes having parent-child relationships by recursively splitting a volumetric space containing the point cloud into sub-volumes each associated with a node of the octree-based structure. The method includes: determining eligibility of planar mode for a present node to be encoded for at least two directions; in the case of eligibility of planar mode in at least two directions of the present node, determining one planar flag indicating planar context information for the at least two directions; and entropy encoding occupancy of the present node based on the determined planar context information to produce encoded data for the bitstream.