基于表情捕捉的数字人面部绑定生成方法

By real-time acquisition and optimization of digital human facial binding methods, the problems of low binding efficiency and unnatural expressions in existing technologies have been solved, achieving efficient and natural digital human facial movements, which are suitable for film and television, virtual live streaming and interactive games.

CN121214518BActive Publication Date: 2026-07-17ZHEJIANG VERSATILE MEDIA

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ZHEJIANG VERSATILE MEDIA
Filing Date
2025-09-26
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing digital human facial binding methods rely on manual adjustments or preset templates, resulting in low binding efficiency, poor flexibility, inability to capture subtle changes in facial expressions, and stiff and unnatural expressions, making it difficult to meet the requirements for high realism.

Method used

Facial data is collected in real time by facial expression capture devices, facial expression feature vectors are extracted, facial motion trajectory fitting and binding rule generation are performed, and the topological structure of the digital human model is combined for mapping and optimization to generate optimized facial binding data to drive the digital human's facial movements.

Benefits of technology

It achieves delicate and natural facial expressions in digital humans, improves binding efficiency and adaptability, enhances the performance of digital humans in film, virtual live streaming and interactive games, and reduces manual operation costs.

✦ Generated by Eureka AI based on patent content.

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Abstract

本发明涉及数字人面部技术领域,公开了基于表情捕捉的数字人面部绑定生成方法。该方法通过表情捕捉设备,实时采集目标对象面部表情数据,获取面部细微运动信息;对采集数据进行特征提取,滤除冗余信息后得到反映面部运动关键特征的表情特征向量集合;依据该集合拟合面部连续运动轨迹,生成符合真实人体运动规律的初始绑定规则;将其映射至数字人模型面部拓扑结构,生成适配模型的初始面部绑定数据;对初始数据进行系统性优化,修正运动参数问题,得到优化面部绑定数据;用优化数据驱动数字人模型面部运动。该方法可让数字人表情更自然、运动更流畅,减少人工操作,提升绑定效率,适用于影视、虚拟直播、互动游戏等场景。
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