Point Cloud Encoding Using Patch Axis Determination
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Solution Overview
Problem
Existing technologies face challenges in efficiently encoding and decoding large-scale point cloud data, which is collected by advanced 3D sensors.
Innovation Solution
A method for point cloud encoding and decoding that involves obtaining description information of a bounding box size and a normal axis of a patch in the point cloud, using this information to determine tangent and bitangent axes, and encoding these axes into a bitstream to improve encoding and decoding performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional point cloud encoding methods are used, then the encoding process is simple, but the encoding efficiency is low and bit overheads are high
Solution Approach 1:
The patent divides the point cloud into multiple patches, where each patch is processed independently to determine its projection direction and arrangement in the occupancy map. This segmentation allows for optimized encoding of each patch while maintaining overall efficiency, resolving the contradiction between simple processing and high encoding efficiency.
Solution Approach 2:
The patent dynamically determines the projection direction and arrangement of each patch based on its specific characteristics and the overall point cloud structure. This dynamic adaptation optimizes the encoding process for each patch, improving overall encoding efficiency without requiring a completely complex fixed system.
2Loss of information
If point cloud data is encoded without optimization, then the encoding process is fast, but the bit overheads are high and decoding performance is poor
Solution Approach 1:
The patent changes key parameters including the projection direction of each patch and the arrangement order in the occupancy map based on patch characteristics and bounding box information. These parameter optimizations reduce bit overheads by improving compression efficiency while maintaining acceptable encoding speeds through systematic parameter determination.
3Productivity
If patches are arranged in a fixed manner in the occupancy map, then the encoding process is simple, but the compression performance is suboptimal
Solution Approach 1:
The patent implements dynamic patch arrangement where the projection direction and position of each patch in the occupancy map is determined based on its normal vector and the bounding box description. This dynamic arrangement optimizes compression performance by adapting to the specific geometry of each patch while following a systematic procedure that does not excessively increase complexity.
Data Source
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AI summary
Embodiments of this application relate to the field of encoding and decoding technologies, and disclose a point cloud encoding method, a point cloud decoding method, an encoder, and a decoder, to provide technical solutions for effectively encoding and decoding point cloud data. The point cloud encoding method includes: obtaining description information of a bounding box size of a to-be-encoded point cloud and a normal axis of a to-be-encoded patch patch in the to-be-encoded point cloud, where the description information of the bounding box size of the to-be-encoded point cloud and the normal axis of the to-be-encoded patch are used to determine a tangent axis of the to-be-encoded patch and a bitangent axis of the to-be-encoded patch; and encoding a syntax element into a bitstream, where the syntax element includes an index of the normal axis of the to-be-encoded patch and information used to indicate the description information of the bounding box size of the to-be-encoded point cloud, and the syntax element is used to indicate the tangent axis of the to-be-encoded patch and the bitangent axis of the to-be-encoded patch.