Point Cloud Tiling Across Video and Atlas Frames for Compression
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Point clouds require significant bandwidth for transmission due to their large bitrate, and existing hardware solutions are expensive and not widely available, while conventional video codecs are not designed to encode and decode 3D content effectively.
Innovation Solution
Convert 3D point clouds into 2D representations using video frames, which are then compressed using existing 2D video codecs, allowing for transmission and reconstruction without specialized hardware, and enable partial decoding of the bitstream for efficient rendering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If point clouds are compressed using specialized hardware, then compression efficiency and quality are improved, but device complexity and cost increase
Solution Approach 1:
The patent uses 2D video codec technology (copying existing mature technology) to compress point cloud data instead of developing specialized compression hardware. The point cloud is converted into 2D video frame representations that can be processed by conventional video codecs, eliminating the need for complex dedicated compression hardware while maintaining acceptable compression quality
Solution Approach 2:
The invention makes conventional 2D video codecs perform the function of 3D point cloud compression by representing point cloud data in 2D video frame format. This allows existing video coding hardware and software to handle point cloud compression without requiring specialized 3D compression equipment, achieving multi-functionality of existing systems
2Reliability
If point clouds are transmitted uncompressed, then data quality is preserved, but bandwidth requirements increase significantly
Solution Approach 1:
The patent changes the representation parameters of point cloud data by converting 3D point coordinates into 2D video frame parameters (pixels, blocks, transform coefficients). This parameter transformation enables the use of efficient 2D video compression algorithms that significantly reduce the quantity of data transmitted while preserving the essential visual information of the point cloud
3Device complexity
If conventional 2D video codecs are used to compress point clouds, then device complexity is reduced, but encoding and decoding effectiveness for 3D content deteriorates
Solution Approach 1:
The patent applies dimensionality change by representing 3D point cloud data in 2D video frame space. The point cloud coordinates (x, y, z) are transformed into 2D video frame coordinates with depth information encoded as pixel values or separate depth maps. This dimensional transformation allows conventional 2D video codecs to process 3D content effectively, achieving good encoding effectiveness without complex 3D-specific hardware
Data Source
AI summary
A method for point cloud encoding includes generating, for a three-dimensional (3D) point cloud, video frames and atlas frames that includes pixels representing information about the 3D point cloud, wherein atlas tiles represent partitions in the atlas frames and video tiles represent partitions in the video frames. The method also includes setting a value for a syntax element according to relationships between sizes of the video tiles and sizes of the atlas tiles. The method further includes encoding the video frames and the atlas frames to generate video sub-bitstreams and an atlas sub-bitstream, respectively. Additionally, the method includes generating a bitstream based on the atlas sub-bitstream, the video sub-bitstreams, and the syntax element and transmitting the bitstream.