Point Cloud Frame Decoding with Multi-Attribute Headers
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Solution Overview
Problem
The existing decoding indication methods for point cloud frames are single and inflexible, leading to inadequate encapsulation and transmission of point cloud media files, which hinders efficient storage, transmission, and standardization of large-scale point cloud data.
Innovation Solution
Implementing a data processing method for point cloud media that includes multiple attribute headers in the decoding indication information, allowing for flexible encapsulation and transmission of point cloud frames, and utilizing a data processing apparatus with processing circuitry to manage this process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single attribute header is used in decoding indication information, then the structure is simple, but the encapsulation and transmission flexibility of point cloud media files is insufficient
Solution Approach 1:
The attribute data is segmented into multiple attribute headers, each representing different attribute types or parameter groups. This segmentation allows selective encoding and transmission of different attribute sets, enhancing flexibility while maintaining manageable complexity through structured organization
Solution Approach 2:
The patent introduces a new dimension to the decoding indication information by adding multiple attribute headers with different attribute identifiers. This transforms the single-dimension structure into a multi-dimensional framework, enabling more versatile encapsulation and transmission options without proportionally increasing complexity
2Productivity
If all attribute data is included in a single point cloud attribute slice, then the storage is simple, but the transmission efficiency and adaptability to different application requirements are reduced
Solution Approach 1:
The attribute data slice is segmented into multiple attribute data groups, each associated with specific attribute headers. This segmentation enables selective transmission of only the attribute data needed for particular applications, improving transmission efficiency while organizing complexity through clear groupings
Solution Approach 2:
Different attribute data groups are organized with different qualities or levels of detail based on their specific requirements. This allows optimized transmission where critical attributes receive higher priority or more detailed encoding, improving overall transmission efficiency while managing data structure complexity through differentiated organization
Data Source
AI summary
In a data processing method for a point cloud media, a media file of the point cloud media is obtained. The media file includes stream data of a plurality of point cloud frames and decoding indication information of each of the plurality of point cloud frames. The decoding indication information of each of the plurality of point cloud frames includes at least two attribute headers. Each of the at least two attribute headers includes attribute identifier information. The point cloud media is processed based on the stream data and the decoding indication information.