Adaptive Occupancy Map Precision for Point Cloud Compression
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Solution Overview
Problem
Existing point cloud compression technologies face inefficiencies in adapting occupancy precision values, leading to suboptimal bitstream transmission and reconstruction quality due to fixed default values or user-defined settings that may not suit various compression scenarios.
Innovation Solution
An adaptive selection mechanism for occupancy precision values based on a quantization parameter (QP), allowing for different precision values depending on the QP threshold, enabling dynamic subsampling and upsampling of occupancy maps during point cloud encoding and decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a fixed default occupancy precision value is used, then the encoding and decoding process is simple, but the bitstream efficiency and reconstruction quality are suboptimal for various compression scenarios
Solution Approach 1:
The occupancy precision value is changed from a fixed default to a dynamic value that adapts based on the quantization parameter (QP). The encoder selectively applies different occupancy precision values (first, second, or third value) depending on the QP range, allowing the system to optimize for both simplicity and quality across different compression scenarios
Solution Approach 2:
The patent changes the occupancy precision parameter based on the quantization parameter (QP) conditions. When QP is below a first threshold, a first occupancy precision value is used; when QP is between the first and second thresholds, a second occupancy precision value is used; and when QP is above the second threshold, a third occupancy precision value is used. This parameter adaptation resolves the contradiction by allowing the system to maintain simplicity when quality requirements are low while improving reconstruction quality when higher bitrates are available
2Adaptability or versatility
If a user-defined occupancy precision value is used, then flexibility is improved, but the complexity of determining the appropriate value increases
Solution Approach 1:
The system uses the quantization parameter (QP) as feedback to automatically determine the appropriate occupancy precision value. The encoder monitors the QP value and selectively applies different occupancy precision values based on predefined QP thresholds, eliminating the need for manual user input while maintaining adaptability across different compression scenarios
Solution Approach 2:
The encoding system automatically selects the appropriate occupancy precision value based on the QP condition without requiring external user input. The system serves itself by using its own encoding parameters (QP) to determine the optimal occupancy precision, thereby maintaining flexibility while reducing the complexity of value selection
3Measurement precision
If high occupancy precision is used, then reconstruction quality is improved, but the bitrate increases
Solution Approach 1:
The patent dynamically changes the occupancy precision parameter based on the quantization parameter (QP) to optimize the bitrate-quality tradeoff. By applying different occupancy precision values (first, second, or third) according to QP thresholds, the system achieves high reconstruction quality when bitrate is available while maintaining efficiency when bitrate is constrained
Solution Approach 2:
The occupancy precision is made dynamic rather than fixed, allowing the system to adapt to different bitrate conditions. The encoder selectively applies higher occupancy precision values when the QP indicates higher bitrate availability, and lower precision values when bitrate is constrained, thereby resolving the contradiction between precision and bitrate
Data Source
AI summary
An encoding device, a method of encoding, and decoding device for point cloud compression of a 3D point cloud. The encoding device is configured to generate, for the three-dimensional (3D) point cloud, at least a set of geometry frames and a set of occupancy map frames for points of the 3D point cloud. The encoding device is also configured to select an occupancy precision value based on a quantization parameter (QP) associated with at least one generated geometry frame in the set of geometry frames, subsample at least one occupancy map frame in the set of occupancy map frames based on the selected occupancy precision value, and encode the set of geometry frames and the set of occupancy map frames into a bitstream for transmission.