3D Point Cloud Octree Decoding With Adaptive Triangle Voxelization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing point cloud compression technologies struggle to achieve high accuracy in reconstructing 3D point clouds, particularly for dense and dynamic AR/VR applications, due to limitations in existing compression schemes that fail to handle complex geometries and require high bandwidth, leading to inefficiencies in real-time transmission.
Innovation Solution
A method for decoding and encoding 3D point clouds using an octree structure and TriSoup encoding, where triangles are extended along their sides based on a sampling distance to enhance voxelization accuracy, employing an adaptive halo parameter to ensure comprehensive reconstruction of the point cloud geometry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional compression schemes are used for point clouds, then bandwidth requirements are reduced, but reconstruction accuracy deteriorates
Solution Approach 1:
The patent applies segmentation by dividing the point cloud into octree structures and further segmenting surfaces into triangular patches. This hierarchical segmentation allows efficient compression at different levels of detail, enabling bandwidth reduction while maintaining reconstruction accuracy through selective refinement of important geometric features.
Solution Approach 2:
The patent changes parameters by introducing adaptive sampling distances and varying triangle extension lengths based on local geometric complexity. By dynamically adjusting these parameters rather than using fixed values, the system achieves better compression efficiency without sacrificing reconstruction accuracy in critical areas.
2Measurement precision
If triangle extension is applied to all triangles, then voxelization accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent applies local quality by extending triangles only in regions where geometric complexity or sampling density requires it, rather than uniformly extending all triangles. This selective approach improves voxelization accuracy where needed while avoiding unnecessary computational overhead in simpler regions.
Solution Approach 2:
The patent uses partial action by applying triangle extension only to a subset of triangles that benefit most from it, determined by local geometric criteria. This partial application achieves sufficient voxelization accuracy without the full computational cost of extending every triangle.
3Measurement precision
If adaptive halo parameter is used, then sampling errors are reduced, but encoding complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing the adaptive halo parameter values during the encoding phase. This preliminary computation allows the decoder to use these pre-determined values without performing complex calculations, thereby reducing sampling errors while keeping the overall system complexity manageable.
Solution Approach 2:
The patent uses self-service by having the encoding process automatically determine and embed the adaptive halo parameters into the bitstream based on the actual geometric content. The system serves itself by generating the necessary control parameters from the data being encoded, reducing the need for external configuration or manual parameter tuning.
Data Source
AI summary
A system and method for encoding and decoding the geometry of 3D point clouds using octree-based data structures are disclosed. The method involves encoding and decoding bitstreams containing octree structure information and vertex data, including the presence and position of vertices on cuboid edges corresponding to leaf nodes. The decoding process determines triangles connecting vertices within each cuboid, which are voxelized to reconstruct the 3D point cloud. To enhance voxelization accuracy, triangles may be extended along one or more sides based on a sampling distance parameter (dsampldsampl) or adaptive halo parameters. The encoding process utilizes similar principles to encode the octree structure and vertex information, supporting geometry reconstruction with high fidelity. The system employs the Möller-Trumbore algorithm and barycentric coordinate calculations with constraints based on dsampldsampl for voxelization. Extensions may include fixed or adaptive parameters encoded within the bitstream.