三维空间中的面部表情生成

P. K. S. Udana, A. Dharmarathne
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引用次数: 0

摘要

面部表情是人们协调对话、交流情感以及其他心理、社会和生理线索的最有力的资源之一。由于人类在游戏、电影、虚拟化身和社交等许多领域对面部表情的高度敏感性,机器人试图模仿这些面部表情来增加其人造人体模型的真实感。提出了一种将比例映射技术与差分特征添加机制相结合的三维网格模型面部表情生成方法。以三维点云数据为输入,采用去尖峰和下采样等预处理技术去除噪声点和不需要的数据点,提高构造模型的平滑度。然后采用2.5D网格重建算法生成三维人脸网格。最后提出了应用于生成的人脸网格的技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Facial Expression Generation in 3D Space
Facial expression is one of the most powerful resources for people to coordinate conversation and communicate emotions and other mental, social, and physiological cues. Because of human's high sensitivity for facial expressions in many areas such as game, movie, avatars and social robot tries to mimic these facial expressions to their artificial human models to increase realistic feature. This paper proposes a novel methodology of combining ratio mapping technique and difference feature adding mechanism to generate facial expressions for mesh models in 3D space. A 3D point cloud data is taken as the input and preprocessing techniques such as spike removing and down sampling are applied to remove noise points and unwanted data points to improve the smoothness of construction model. Then a 2.5D mesh reconstruction algorithm is applied to generate a 3D face mesh. In the final stage proposed techniques applied to the generated face meshes.
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