Point Cloud Coding Using Capturing Laser Identification
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Solution Overview
Problem
Current point cloud coding techniques face inefficiencies in compressing point cloud data, particularly for LIDAR capturing data, as they do not effectively utilize prior information about laser beam passage to determine isolated points and fail to consider eligibility conditions in azimuthal directions.
Innovation Solution
The proposed methods determine the capturing laser for each node in a point cloud frame and assess whether nodes are passed by a single laser beam, applying specific coding modes and using angular information to improve compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional point cloud coding techniques are used, then the coding process is simple, but the coding efficiency is insufficient
Solution Approach 1:
The patent segments the point cloud data into nodes representing spatial partitions, and further segments the coding process by determining capturing lasers for each node individually. This allows different coding strategies to be applied to different nodes based on their laser passage characteristics, improving overall coding efficiency while managing complexity through structured division.
Solution Approach 2:
The patent performs preliminary determination of capturing lasers for each node before the actual coding process. By pre-identifying which laser captured each node and whether it was passed by a single laser beam, the coding process can directly apply optimized coding modes without complex real-time analysis, thus improving efficiency while keeping the overall process manageable.
2Measurement precision
If prior information about laser beam passage is not utilized, then the coding process is straightforward, but isolated points cannot be accurately identified
Solution Approach 1:
The patent performs preliminary determination of capturing lasers for each node before the actual coding process. By pre-identifying which laser captured each node and whether it was passed by a single laser beam, the coding process can directly apply optimized coding modes without complex real-time analysis, thus improving efficiency while keeping the overall process manageable.
Solution Approach 2:
The patent uses the determined capturing laser information as feedback to guide the coding process. By feeding back the single-laser-passage determination to the coding mode selection, the system accurately identifies isolated points and applies appropriate coding strategies, improving identification accuracy while maintaining process coherence.
3Productivity
If coding modes are not optimized based on laser beam passage, then the coding process is uniform, but compression efficiency is reduced
Solution Approach 1:
The patent applies different coding modes to different nodes based on their local characteristics - specifically whether each node was passed by a single laser beam. This local optimization allows isolated points (single laser passage) to use one coding mode while non-isolated points use another, improving compression efficiency without requiring complex global optimization.
Solution Approach 2:
The patent changes the coding mode parameter based on the determined capturing laser characteristics. By switching between different coding modes depending on whether a node was passed by a single laser beam or multiple beams, the system optimizes compression efficiency for different types of points while managing complexity through clear parameter-based classification.
Data Source
AI summary
Embodiments of the present disclosure provide a solution for point cloud coding. A method for point cloud coding is proposed. The method comprises: determining, during a conversion between a current frame of a point cloud sequence and a bitstream of the point cloud sequence, a capturing laser which captures a node of the current frame, the node representing a spatial partition of the current frame; and performing the conversion based on the capturing laser.