Point Cloud Chunking for Video Patch Packing Efficiency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current technologies face challenges in efficiently compressing point clouds for real-time communications in virtual reality and dynamic mapping applications, requiring effective lossy and lossless compression methods to reduce data volume while maintaining quality.
Innovation Solution
The method involves dividing an input point cloud into chunks, generating patches based on these chunks, packing the patches into images, and generating a video stream from these images, leveraging existing video codecs to compress geometry, occupancy, and texture as separate video sequences, with metadata compression to support efficient interpretation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If point cloud data is compressed using traditional methods, then data volume is reduced, but compression efficiency and quality are insufficient for real-time applications
Solution Approach 1:
The point cloud is divided into multiple patches, and each patch is processed independently through encoding into 2D image data. This segmentation enables parallel processing and more efficient compression while maintaining local geometric details, resolving the contradiction between compression efficiency and quality by allowing targeted optimization of each patch.
Solution Approach 2:
The patent transforms 3D point cloud data into 2D image representations through patch encoding. This dimensional transformation allows the use of mature 2D video coding standards (like H.266/VVC) to compress point cloud data, significantly improving compression efficiency while preserving essential visual information through the patch-based approach.
2Productivity
If point cloud data is divided into many small patches, then compression efficiency improves, but processing complexity increases
Solution Approach 1:
The point cloud is segmented into patches that are then encoded independently. This segmentation strategy improves compression efficiency by enabling parallel processing and better adaptation to local features, while the standardized patch encoding process manages complexity through systematic handling of each patch.
Solution Approach 2:
The patent uses a universal patch encoding framework that can handle different point cloud configurations using the same encoding pipeline. This multi-functional approach manages processing complexity by applying a standardized method across all patches, regardless of their specific characteristics.
3Ease of manufacture
If existing video codecs are used to compress point cloud data, then implementation becomes simpler, but compression performance for 3D data is limited
Solution Approach 1:
The patent converts 3D point cloud data into 2D image patches that can be processed by conventional video codecs. This dimensional transformation enables the use of well-established, easily implemented video coding standards while improving compression performance through the patch-based representation that better suits 2D codec architectures.
Solution Approach 2:
The patch encoding process acts as an intermediary that transforms 3D point cloud data into a form suitable for 2D video codecs. This intermediary step bridges the gap between 3D data structures and 2D coding standards, enabling simple implementation using existing codecs while achieving better compression performance through the transformation.
Data Source
AI summary
A method and apparatus for encoding a video stream using video point cloud coding, the decoding including obtaining an input point cloud; dividing the input point cloud into a plurality of chunks, including a first chunk including a first plurality of points and a second chunk including a second plurality of points; generating a first plurality of patches based on the first plurality of points; generating a second plurality of patches based on the second plurality of points; packing the first plurality of patches and the second plurality of patches into an image; and generating the video stream based on the image.