Point Cloud Compression via 2D Frame Projection
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Solution Overview
Problem
Point clouds require significant bandwidth for transmission due to their large size and complexity, necessitating efficient compression techniques that differ from traditional 2D multimedia compression methods.
Innovation Solution
The use of image/video codecs to compress and decompress point clouds by generating multiple 2D frames representing the geometry and texture of point clouds, along with an occupancy map, to create a compressed bitstream for efficient transmission and rendering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If point clouds are transmitted uncompressed, then the quality and integrity of the 3D data is preserved, but the bandwidth requirements and transmission time increase significantly
Solution Approach 1:
The point cloud data is segmented into multiple 2D depth map frames, where each frame represents a portion of the 3D space. This segmentation allows the data to be processed and transmitted more efficiently while maintaining the ability to reconstruct the complete point cloud, thus reducing bandwidth requirements without sacrificing data integrity.
Solution Approach 2:
The patent transforms the 3D point cloud data into a series of 2D depth map frames by projecting points onto 2D planes. This dimensionality reduction from 3D to 2D significantly compresses the data size for transmission, while the occupancy map and frame structure preserve the necessary 3D spatial information for accurate reconstruction.
2Ease of manufacture
If traditional 2D multimedia compression methods are used for point clouds, then the compression process is simple and compatible with existing codecs, but the compression efficiency is insufficient for 3D data structures
Solution Approach 1:
The patent makes existing 2D video codecs universal for 3D point cloud compression by adapting the encoding process. Instead of creating entirely new 3D compression algorithms, the system uses standard 2D codecs to encode depth map frames, leveraging their proven efficiency and wide compatibility while achieving adequate compression for point cloud data.
Solution Approach 2:
The patent introduces 2D depth map frames as an intermediary representation between the original 3D point cloud and the compressed bitstream. These depth maps serve as a bridge that can be processed by conventional 2D video codecs, enabling efficient compression while preserving the essential 3D geometric information needed for reconstruction.
3Quantity of substance
If multiple 2D frames and occupancy maps are generated to represent point clouds, then the bandwidth for transmission is reduced, but the complexity of the encoding and decoding processes increases
Solution Approach 1:
The patent creates 2D copies (depth map frames) of the 3D point cloud data from different viewing angles or depth planes. These 2D copies are easier to compress and transmit than the original 3D data. The occupancy map acts as a companion copy that indicates which regions contain valid point data, enabling efficient reconstruction without requiring complex transformations.
Data Source
AI summary
An decoding device, an encoding device and a method for point cloud encoding is disclosed. The method includes generating, from a three-dimensional point cloud, multiple two-dimensional frames, the two-dimensional frames including at least a first frame representing a geometry of points in the three-dimensional point cloud and a second frame representing texture of points in the three-dimensional point cloud. The method also includes generating an occupancy map indicating locations of pixels in the two-dimensional frames that represent points in the three-dimensional point cloud. The method further includes encoding the two-dimensional frames and the occupancy map to generate a compressed bitstream. The method also includes transmitting the compressed bitstream.