Avatar Physical Model Mapping for Automatic VR Calibration
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Solution Overview
Problem
Existing technologies for representing users in virtual environments using control devices like webcams and AR/VR devices lack accuracy due to reliance on average user representations, requiring manual calibration and limited data capture, which is inefficient and user-intervention dependent.
Innovation Solution
A method for obtaining and rendering avatars in virtual environments using personalized physical properties of users, including body models and connection data, to enhance accuracy and automate calibration without user intervention, using formats like AJIF and glTF to encode avatar and body models with physical properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If average user representation is used for avatar control, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The system performs preliminary action by automatically capturing user physical properties and calibrating the avatar model before actual use. The calibration data is pre-computed and stored, eliminating the need for manual setup while enabling precise personalized avatar representation from the first use.
Solution Approach 2:
The system implements self-service by automatically capturing user physical properties and performing calibration without manual intervention. The avatar model self-adjusts to match the user's body characteristics, eliminating the need for users to manually configure or calibrate their avatars.
2Measurement precision
If manual calibration is required for accurate avatar representation, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs automatic calibration by capturing user physical properties and adjusting the avatar model without manual intervention. This self-calibration process eliminates the time users would otherwise spend on manual setup while maintaining high representation accuracy.
Solution Approach 2:
The system replaces manual calibration procedures with an automated computational process. Instead of users manually adjusting avatar parameters, the system uses algorithms to capture physical properties and automatically configure the avatar model, substituting mechanical/manual operations with automated digital processing.
3Measurement precision
If capture devices are calibrated for specific users, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system achieves universality by designing a capture device that can automatically adapt to any user without requiring user-specific configuration. The same device serves all users by automatically capturing their physical properties and adjusting parameters, eliminating the need for individual calibration procedures while maintaining high precision.
Solution Approach 2:
The capture device performs self-calibration by automatically detecting and adapting to each user's physical characteristics. Instead of requiring manual configuration for each user, the device self-adjusts its parameters based on captured data, reducing operational complexity while maintaining measurement precision.
Data Source
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AI summary
Some embodiments of a method may include: obtaining a first avatar model corresponding to a first avatar; obtaining physical properties of the first avatar model; and rendering, in a virtual environment, the first avatar using the first avatar model and the physical properties of the first avatar model. Some embodiments of the method may further include obtaining a mapping of physical properties of the user to the first avatar, wherein rendering the first avatar further uses the mapping of physical properties.