用于面部行为研究的三维面部表情数据库

L. Yin, Xiaozhou Wei, Yi Sun, Jun Wang, Matthew J. Rosato
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引用次数: 1285

摘要

传统上,人类面部表情的研究要么使用二维静态图像,要么使用二维视频序列。基于2d的分析无法处理大的姿势变化。尽管三维建模技术已广泛应用于三维人脸识别和三维人脸动画,但利用三维距离数据进行三维面部表情识别的研究却很少。阻碍此类研究的一个主要因素是缺乏公开可用的3D面部表情数据库。在本文中,我们提出了一个新开发的3D面部表情数据库,其中包括来自100个受试者的2500个模型的3D面部表情原型形状和2D面部纹理。这是为研究界提供3D面部表情数据库的第一次尝试,其最终目标是促进情感计算的研究,增加对面部行为和人类面部表情固有的精细3D结构的一般理解。新的数据库可以为算法的评估、比较和评价提供有价值的资源
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A 3D facial expression database for facial behavior research
Traditionally, human facial expressions have been studied using either 2D static images or 2D video sequences. The 2D-based analysis is incapable of handing large pose variations. Although 3D modeling techniques have been extensively used for 3D face recognition and 3D face animation, barely any research on 3D facial expression recognition using 3D range data has been reported. A primary factor for preventing such research is the lack of a publicly available 3D facial expression database. In this paper, we present a newly developed 3D facial expression database, which includes both prototypical 3D facial expression shapes and 2D facial textures of 2,500 models from 100 subjects. This is the first attempt at making a 3D facial expression database available for the research community, with the ultimate goal of fostering the research on affective computing and increasing the general understanding of facial behavior and the fine 3D structure inherent in human facial expressions. The new database can be a valuable resource for algorithm assessment, comparison and evaluation
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