3D Face Landmark Masking for Metaverse Identity Protection
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Solution Overview
Problem
Existing metaverse applications expose realistic 3D face models, leading to potential identity theft risks by directly exposing identifiable information to the public without adequate protection mechanisms, compromising the intimacy and realism of in-person interactions.
Innovation Solution
Implement a computer-implemented method to dynamically mask 3D face landmarks based on the intimacy level between users, using a noise estimator to iteratively denoise randomly selected landmarks, preserving realism and intimacy while concealing personally identifiable features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If realistic 3D face models are exposed in the metaverse, then interaction realism and intimacy are improved, but personally identifiable information security deteriorates
Solution Approach 1:
The patent applies local quality by selectively masking only specific facial landmarks (eyes, nose, mouth) while preserving other facial features. This allows the avatar to maintain overall realism and recognizability for intimate interactions while protecting personally identifiable information by obscuring only the most sensitive features.
Solution Approach 2:
The masking system dynamically adjusts which landmarks are masked based on the intimacy level between users. As intimacy increases, fewer landmarks are masked, allowing the face to become progressively more recognizable. This dynamic approach resolves the contradiction by adapting the level of protection based on the interaction context.
2Object-affected harmful factors
If more facial landmarks are masked, then personally identifiable information protection is improved, but interaction realism and intimacy deteriorate
Solution Approach 1:
The system dynamically determines the number of landmarks to mask based on the intimacy level between users. The intimacy score, calculated from interaction history, automatically adjusts the masking intensity, ensuring that protection levels adapt to the relationship context without manual intervention.
Solution Approach 2:
Rather than uniformly masking the entire face, the system selectively masks only specific critical landmarks while preserving other features. This localized approach maintains sufficient realism for intimate interactions while providing adequate protection against identity theft.
3Measurement precision
If manual intimacy setting is used, then intimacy control precision is improved, but system complexity and user burden increase
Solution Approach 1:
The system automatically calculates intimacy levels by analyzing interaction history between users, eliminating the need for manual user input. The system serves itself by deriving the intimacy metric from observable interaction patterns, reducing user burden while maintaining measurement precision.
Solution Approach 2:
The system continuously monitors interaction patterns and uses this feedback to dynamically adjust the intimacy score. This feedback loop allows the system to automatically refine its understanding of user relationships without requiring explicit user input, reducing complexity while maintaining accuracy.
Data Source
AI summary
Aspects of the invention include techniques for intimacy-based masking of three dimensional (3D) face landmarks within a metaverse. A non-limiting example method includes determining a degree of intimacy R between a first user and a second user responsive to a first avatar of the first user being observed by a second avatar of the second user in a virtual environment. An initial set of M landmarks of a feature of the first avatar is determined and N landmarks are randomly selected from M for masking. The N landmarks are replaced with random noise sampled with a unit normal distribution to define a set of noised landmarks X that are then iteratively denoised to define a set of denoised landmarks D. A masked version of the first avatar is presented to the second user by modifying the feature of the first avatar with the set of denoised landmarks D.