Multi-Resolution Point Cloud Distribution via Sieve Segmentation
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Solution Overview
Problem
The distribution of multi-resolution point clouds poses a challenge due to the large digital representation size, as creating separate representations for each expected resolution results in a significantly larger volume than the original, and existing solutions fail to adequately protect these assets from piracy while controlling access.
Innovation Solution
A point cloud distribution system that applies sieve functions to generate disjointed partial point clouds, scrambles them using secret keys, and distributes only the necessary scrambled point clouds and keys to control access, allowing for secure and efficient delivery of different resolutions without increasing the overall content size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If separate point cloud representations are created for each expected resolution, then access control and piracy protection are improved, but the overall content size increases significantly
Solution Approach 1:
The patent divides the full-resolution point cloud into multiple disjointed partial point clouds at different resolutions using sieve functions. Each partial point cloud is then encrypted with a corresponding secret key. This segmentation allows the system to provide access control at different resolution levels without requiring separate complete point cloud representations, thereby reducing overall content size while maintaining security.
Solution Approach 2:
The patent implements a nested structure where lower-resolution partial point clouds are contained within the higher-resolution full point cloud. The sieve functions extract subsets of points from the full-resolution cloud to create nested representations at different resolutions. This nesting allows clients to access only the resolution level they are authorized for, reducing the effective content size transmitted and stored while maintaining comprehensive protection.
2Adaptability or versatility
If multiple point cloud representations at different resolutions are created, then distribution control is improved, but the data volume increases
Solution Approach 1:
The patent segments the point cloud data into disjointed partial point clouds at different resolutions using sieve functions. Each segment is encrypted with a specific secret key corresponding to its resolution level. This segmentation enables the distribution system to control access at different resolution levels without creating separate complete representations, thereby maintaining distribution control while reducing overall data volume.
Solution Approach 2:
The patent applies local quality by providing different resolution levels of point cloud data to different clients based on their authorization. Each client receives only the partial point clouds corresponding to their authorized resolution level, rather than all resolutions. This local quality approach maintains versatile distribution control while minimizing the total data volume transmitted to each client.
Data Source
AI summary
Distributing different resolution point clouds of a full resolution point cloud, including: applying a plurality of sieve functions to the full resolution point cloud (PC) to generate a plurality of partial point clouds (PCs), wherein the partial PCs are disjointed elements of the full resolution PC; scrambling each partial PC of the plurality of partial PCs using a respective one of a plurality of secret keys; and distributing at least one scrambled PC and a selected secret key to an intended recipient, wherein the selected secret key is selected based on an appropriate resolution determined for the intended recipient.