3D Point Cloud Compression via 2D Projection
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Solution Overview
Problem
Conventional point cloud compression methods are inefficient and require significant time to generate new codecs, necessitating a method to utilize legacy codecs and networks for efficient data compression.
Innovation Solution
The method involves voxelizing points in a 3D image, grouping them into segments, projecting these segments into 2D images, packing and encoding the 2D images using a legacy 2D video compression scheme, and transmitting the encoded data, allowing for efficient compression and reconstruction of 3D images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional point cloud compression methods are used, then data compression is achieved, but significant time is required to generate new codecs and processing loads are high
Solution Approach 1:
The patent transforms 3D point cloud data into 2D image data through voxelization and projection operations. By converting the data structure from three-dimensional point coordinates to two-dimensional image representations, the system can leverage existing 2D video compression codecs, thereby avoiding the time-consuming development of new 3D compression algorithms while maintaining effective compression capabilities.
Solution Approach 2:
The patent creates 2D image copies or projections from the original 3D point cloud data. These 2D representations serve as intermediaries that can be processed by成熟的 2D compression algorithms. The copying process involves projecting 3D points onto 2D planes, creating representations that preserve essential visual information while enabling the use of existing compression technology.
2Productivity
If new codecs are developed for point cloud compression, then compression performance improves, but development costs and complexity increase
Solution Approach 1:
The patent makes the compression system universal by enabling it to use existing 2D video compression codecs for 3D point cloud data. Instead of creating specialized 3D compression algorithms, the system transforms 3D data into a format compatible with widely-used 2D codecs, thereby reducing development costs and complexity while maintaining compression effectiveness. This multi-functional approach allows a single processing pipeline to handle both 2D and 3D compression needs.
Solution Approach 2:
The patent introduces 2D image projections as intermediary representations between the original 3D point cloud and the compression process. These intermediaries serve as a bridge that allows existing 2D compression algorithms to process 3D data effectively. The intermediary 2D images capture the essential visual information needed for compression while being compatible with mature compression technology.
3Reliability
If point cloud data is processed directly, then 3D information is preserved, but memory resources are excessively consumed
Solution Approach 1:
The patent reduces memory consumption by transforming 3D point cloud data into 2D image representations. This dimensional reduction converts data that requires storing three-dimensional coordinates for numerous points into 2D image arrays that occupy less memory. The transformation maintains essential visual information while significantly reducing the memory footprint, enabling efficient storage and processing of large-scale 3D data.
Data Source
AI summary
A method for transmitting data for a three-dimensional image is provided. The method comprises the steps of: generating a plurality of voxelized points corresponding to a plurality of voxels, respectively, from a plurality of points constituting a three-dimensional image; grouping the plurality of voxelized points into a plurality of segments, wherein each of the plurality of segments includes at least one of the plurality of voxelized points; for each segment, projecting the plurality of points and generating a plurality of two-dimensional images; generating a packed two-dimensional image from the generated plurality of two-dimensional images; decoding data for the packed two-dimensional image, and encapsulating same; and transmitting the decoded and encapsulated data.