XR Hand Scale Estimation Using Mobile Interaction Calibration
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Solution Overview
Problem
Traditional hand-tracking technologies in XR systems are cumbersome and lack accuracy due to scale ambiguity, particularly in mobile settings, where complex setups involving multiple cameras and sensors fail to provide desired simplicity and user flexibility.
Innovation Solution
A method leveraging a user's interaction with a mobile device during setup, using cameras and inertial motion sensors to facilitate initial calibration and ongoing adjustment of hand scale estimations, simplifying the calibration process and enhancing hand-tracking accuracy by deriving accurate scale measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional hand-tracking technologies use multiple cameras and sensors, then measurement precision may improve, but device complexity increases significantly
Solution Approach 1:
The patent extracts the scale calibration function from complex multi-camera systems and implements it using a simple mobile device camera. By taking out the essential calibration task and performing it on a standalone mobile device during setup, the system achieves accurate hand scale estimation without requiring complex multi-camera infrastructure.
Solution Approach 2:
The system performs self-calibration by automatically capturing hand images during mobile device interaction and computing scale factors without user intervention. The calibration process is automated, where the system itself gathers necessary data and computes calibration parameters, eliminating the need for manual setup or complex external equipment.
2Measurement precision
If complex calibration systems are implemented, then measurement precision improves, but ease of operation deteriorates
Solution Approach 1:
The system performs scale calibration as a preliminary action during mobile device setup before the user begins interacting with the XR system. By completing the calibration task in advance during a natural setup process, the system ensures accurate hand scale estimation is available immediately when needed, without requiring complex ongoing calibration procedures.
Solution Approach 2:
The calibration process is designed to be self-service, where the system automatically captures hand images, processes them, and computes scale factors without requiring user expertise or manual intervention. Users simply interact with the mobile device as normal, and the system handles all calibration operations automatically.
3Adaptability or versatility
If traditional hand-tracking is used in mobile settings, then portability is maintained, but measurement precision deteriorates due to scale ambiguity
Solution Approach 1:
The system changes the scale parameter by computing a hand scale factor that transforms 2D mobile device camera images into accurate 3D hand representations. By introducing and applying this scale factor parameter during mobile device interaction, the system resolves scale ambiguity and enables precise hand tracking in mobile settings without sacrificing portability.
Data Source
AI summary
An XR system is provided that enhances user interaction within extended reality environments through precise hand scale estimation. The XR system is configured to capture tracking data of a user's hand as the user interacts with a mobile device. Concurrently, the XR system captures pose data of itself and uses the tracking data and the pose data to determine a reference line segment. This segment aids in calculating three-dimensional distances between node pairs of the user's hand. By employing these measurements, the XR system effectively calculates a hand scale factor that is used for accurately integrating the user's hands into an XR user interface.