Point Cloud Scrambling via Polar Coordinate Radial Translation
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Solution Overview
Problem
Point clouds are vulnerable to piracy, and overprotecting them makes it difficult for legitimate purchasers to sample them before purchase, necessitating a secure yet accessible 'lower quality' representation that preserves visual and geometrical aspects without compromising security.
Innovation Solution
A system that scrambles point clouds in polar coordinates by translating points along a radial axis using a pseudo-random number generator seeded by a secret key, allowing for descrambling to restore the original point cloud while maintaining security and fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If strong protection measures are applied to point clouds, then security against piracy is improved, but the ability to sample and preview the point cloud before purchase deteriorates
Solution Approach 1:
The patent segments the point cloud data into multiple groups and applies different scrambling intensities to different segments. Some segments are heavily scrambled to maintain security, while others are lightly scrambled or unscrambled to allow sampling and preview. This segmentation enables simultaneous protection and accessibility.
Solution Approach 2:
Different regions or portions of the point cloud are assigned different quality levels after scrambling. Critical areas maintain high security with strong scrambling, while non-critical areas use weaker scrambling to enable preview. This local differentiation resolves the contradiction between overall security and sampling capability.
2Reliability
If the point cloud is scrambled to protect security, then piracy prevention is improved, but the visual and geometrical quality of the point cloud deteriorates
Solution Approach 1:
Instead of applying full-strength scrambling to the entire point cloud, the patent applies partial scrambling only to specific segments or portions. This partial action maintains security for protected regions while preserving geometrical fidelity in regions where quality is prioritized, thus resolving the contradiction between security and precision.
3Reliability
If deterministic random translation is applied to scramble points, then security against unauthorized access is improved, but the complexity of the scrambling system increases
Solution Approach 1:
The scrambling system uses the point cloud's own geometric properties (such as point indices, spatial coordinates, or structural features) as inputs to the deterministic random translation function. This self-service approach generates the scrambling sequence from the data itself, eliminating the need for external complex key management systems while maintaining security.
Data Source
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AI summary
Scrambling a point cloud (PC), including: receiving the PC in polar coordinates, wherein each point of the PC includes an index; scrambling each point of the PC by translating each point along a radial axis of the polar coordinates by adding a pseudo-random number (PRN) to each point, wherein the PRN is generated using the index and a secret key.