计算机科学
面部表情
模态(人机交互)
表达式(计算机科学)
人工智能
面子(社会学概念)
计算机视觉
数据库
面部识别系统
模式识别(心理学)
社会科学
社会学
程序设计语言
作者
Lijun Yin,Xiaochen Chen,Yi Sun,Tony Worm,Michael Reale
标识
DOI:10.1109/afgr.2008.4813324
摘要
Face information processing relies on the quality of data resource. From the data modality point of view, a face database can be 2D or 3D, and static or dynamic. From the task point of view, the data can be used for research of computer based automatic face recognition, face expression recognition, face detection, or cognitive and psychological investigation. With the advancement of 3D imaging technologies, 3D dynamic facial sequences (called 4D data) have been used for face information analysis. In this paper, we focus on the modality of 3D dynamic data for the task of facial expression recognition. We present a newly created high-resolution 3D dynamic facial expression database, which is made available to the scientific research community. The database contains 606 3D facial expression sequences captured from 101 subjects of various ethnic backgrounds. The database has been validated through our facial expression recognition experiment using an HMM based 3D spatio-temporal facial descriptor. It is expected that such a database shall be used to facilitate the facial expression analysis from a static 3D space to a dynamic 3D space, with a goal of scrutinizing facial behavior at a higher level of detail in a real 3D spatio-temporal domain.
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