Hand Feature Extraction for XR User Identity Authentication
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Solution Overview
Problem
Existing extended reality (XR) systems face challenges in accurately determining and managing user identities, particularly in multi-user environments where gestures are used for interaction, leading to difficulties in authorizing specific actions and preventing unauthorized access.
Innovation Solution
The system employs hand feature extraction and recognition techniques using sensor data, including 2D image frames, to identify and track users based on hand features such as bounding boxes, keypoints, and chirality, allowing for the determination of user identities and authorization within XR environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If hand feature extraction and recognition techniques are used to identify users in XR environments, then user identity determination accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments the user identification process into distinct stages: hand detection, feature extraction (bounding boxes, keypoints, chirality), feature comparison, and identity determination. This segmentation allows each component to be optimized independently while maintaining overall system accuracy.
Solution Approach 2:
The patent introduces hand features as an intermediary element between the sensor data and user identity. Instead of directly identifying users from complex sensor data, the system extracts intermediate hand features (keypoints, bounding boxes, chirality) that serve as a bridge for more accurate and manageable identity determination.
2Adaptability or versatility
If multiple users are allowed to interact in XR environments, then system versatility is improved, but difficulty in detecting and measuring user identity increases
Solution Approach 1:
The system applies local quality by extracting specific hand features (keypoints, bounding boxes, chirality) from each user's hands rather than attempting to analyze entire body or facial features. This localized approach to hand feature extraction simplifies multi-user identification while maintaining accuracy.
Solution Approach 2:
The patent uses chirality (handedness) as a distinctive characteristic to differentiate between users. By determining whether hands are left or right hands and comparing this property across users, the system creates an additional dimension for user differentiation that simplifies multi-user tracking.
Data Source
AI summary
Techniques for authenticating a user based on hand features includes receiving sensor data of a scene that includes hands, extracting features for at least one of the hands, and determining a first identity associated with the at least one hand based on the extracted features. The user identity may be associated with authentication information such that when a system detects a gesture by the hands, the authentication information is assessed prior to performing an action associated with the gesture. Authenticated users may be used for determining authorized activity for performing an action associated with a gesture, and may be used for collaborative activity among users.