3D Facial Animation Velocity and Acceleration Control
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Solution Overview
Problem
Current facial animation driven by speech recognition often results in unnatural movements due to jerky transitions and errors in speech recognition, such as unintended phonemes being tracked, leading to unnatural facial expressions.
Innovation Solution
A method that limits the velocity and acceleration of a normalized parameter vector mapped to animation node outputs of a 3D model, using mesh blending and weighted key frames to control the transition between visemes, ensuring a natural and smooth facial animation by damping the effect of errors and modeling facial muscle motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If mesh-morphing is used to transition between facial expressions, then the facial animation can be controlled according to speech phonemes, but the transitions appear jerky and unnatural
Solution Approach 1:
The patent applies dynamics by making the morph target positions time-varying rather than static. The system dynamically adjusts the target positions based on the speech phoneme sequence, allowing the face to transition smoothly between expressions over multiple frames rather than jumping abruptly between key frames.
Solution Approach 2:
The patent uses preliminary action by anticipating the next phoneme in the speech sequence and pre-positioning the morph target accordingly. This allows the facial animation to prepare for upcoming transitions, creating smoother and more natural movement patterns that align with the speech rhythm.
2Measurement precision
If the weighting factor for morph targets is changed quickly to match speech phonemes, then the facial animation responds accurately to speech, but the transitions become jerky and unnatural
Solution Approach 1:
The system dynamically adjusts the weighting factors over time rather than changing them instantly. By distributing the weight change across multiple frames and using time-varying morph target positions, the system maintains accurate phoneme-to-viseme mapping while achieving natural transition speeds that match human facial movement.
Solution Approach 2:
The patent implements periodic action by synchronizing the facial animation transitions with the temporal rhythm of speech. The system adjusts the timing and speed of weight changes to match the natural pace of phoneme articulation, creating harmonious coordination between speech and facial movement.
3Measurement precision
If speech recognition errors are corrected by removing unintended phonemes, then the facial animation accuracy improves, but the transitions become more complex and less natural
Solution Approach 1:
The patent converts the harm of speech recognition errors into a benefit by using the errors as cues for natural transition behavior. Instead of simply removing erroneous phonemes, the system uses them to trigger smooth transitions that mimic natural human facial movement, turning the error correction process into an opportunity to enhance the naturalness of the animation.
Solution Approach 2:
The system implements feedback by continuously monitoring the speech recognition output and adjusting the facial animation in real-time. When errors are detected, the system uses feedback mechanisms to correct them while maintaining natural transition patterns, creating a closed-loop system that adapts to speech variations and maintains animation quality.
Data Source
AI summary
Natural inter-viseme animation of 3D head model driven by speech recognition is calculated by applying limitations to the velocity and/or acceleration of a normalized parameter vector, each element of which may be mapped to animation node outputs of a 3D model based on mesh blending and weighted by a mix of key frames.