Avatar Face Tracking With Personalized Feature Size Mapping
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Solution Overview
Problem
Existing face tracking systems fail to accurately map facial expressions of users to avatars, leading to miscommunication and reduced immersion in virtual environments due to facial feature differences among individuals.
Innovation Solution
A face tracking system and method that utilizes a camera and processor to identify facial features, determine their size ranges, and establish a transformation relationship between user and avatar facial features, employing personalized models for precise mapping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a generic face tracking model is used, then the system complexity is low, but the mapping accuracy between user facial expressions and avatar expressions deteriorates
Solution Approach 1:
The system determines size ranges of user facial features and uses these parameter variations to establish transformation relationships. By changing the parameters (size ranges) based on individual user characteristics, the system achieves accurate mapping without requiring overly complex structures.
Solution Approach 2:
The system performs preliminary determination of facial feature size ranges before establishing the transformation relationship. This preliminary action captures individual user characteristics in advance, enabling accurate expression mapping while keeping the overall system structure manageable.
2Measurement precision
If individualized face tracking models are implemented, then the mapping accuracy improves, but the ease of operation deteriorates due to additional calibration steps
Solution Approach 1:
The system automatically determines facial feature size ranges and establishes transformation relationships without requiring manual user input or complex calibration procedures. The self-service approach maintains high mapping accuracy while preserving ease of operation.
Solution Approach 2:
The system uses feedback from captured face images to automatically adjust and determine the transformation relationship. This feedback mechanism enables the system to adapt to individual user characteristics automatically, improving accuracy without burdening the user with complex operations.
3Reliability
If facial feature size ranges are determined and transformation relationships are established, then the immersion improves, but the processing time increases
Solution Approach 1:
The system determines facial feature size ranges and establishes transformation relationships as preliminary steps before actual expression tracking. This preliminary action ensures high immersion quality during usage while allowing for efficient real-time processing.
Solution Approach 2:
The system uses dynamic transformation relationships that are established once but applied continuously. This approach maintains high immersion quality through accurate mapping while minimizing ongoing processing time requirements.
Data Source
AI summary
A face tracking system is provided. The face tracking system includes a camera and a processor. The camera is configured to obtain a face image of a face of a user. The processor is configured to identify a facial feature of the face of the user based on the face image, determine a size range of a size of the facial feature based on the face image, and determine transformation relationship between the facial feature of the face of the user and a virtual facial feature of an avatar corresponding to the facial feature based on the size range of the size of the facial feature and a virtual size range of a virtual size of the virtual facial feature.