Point Cloud Depth Encoding via Occupancy Map Segmentation
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Solution Overview
Problem
Existing technologies face challenges in efficiently compressing and distributing dynamic point clouds while maintaining acceptable quality and minimizing bit-rate consumption.
Innovation Solution
A method involving the assignment of pixel values in an occupancy image to indicate either the storage of depth values in a depth image or the use of a fixed-length codeword representing depth values, along with signaling information about the use of fixed-length codewords and their length.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If depth values are stored for all 3D samples in a depth image, then quality of point cloud representation is improved, but bit-rate consumption increases
Solution Approach 1:
The patent extracts only the necessary depth information by using an occupancy map to identify which 3D sample positions actually contain points. Instead of storing depth values for all possible positions, only the occupied positions are encoded in the depth image, removing redundant data and reducing bit-rate while maintaining quality.
Solution Approach 2:
The patent employs dynamic encoding strategies where the occupancy map is updated based on the actual distribution of 3D samples. The encoding process adapts to the dynamic characteristics of the point cloud data, adjusting which positions require depth storage based on real-time occupancy information.
2Quantity of substance
If compression is increased to reduce bit-rate, then bit-rate consumption is improved, but quality of point cloud representation deteriorates
Solution Approach 1:
The patent segments the point cloud data processing into two distinct stages: first generating an occupancy map that identifies occupied positions, then creating a depth image only for those occupied positions. This segmentation allows efficient compression by eliminating unused space while preserving all necessary quality information.
Solution Approach 2:
The occupancy map serves as an intermediary data structure that bridges the gap between the 3D sample positions and the depth image. It acts as a guide to determine which positions require depth encoding, enabling lossless compression by preventing encoding of empty positions while ensuring all occupied positions are properly represented.
3Productivity
If variable-length codewords are used for depth values, then coding efficiency is improved, but device complexity increases
Solution Approach 1:
The patent performs preliminary encoding by first creating the occupancy map before generating the depth image. This preliminary action identifies all positions that require encoding, allowing the system to use simple fixed-length codewords for those specific positions rather than implementing complex variable-length encoding logic throughout the entire process.
Data Source
AI summary
At least one embodiment relates to a method assigning a pixel value of an occupancy map either indicates that a depth value of at least one 3D sample of a point cloud frame projected along a same projection line is stored as a pixel value of at least one layer or equals a fixed-length codeword representing a depth value of at least one 3D sample projection along said projection line.