Comprehensive database for facial expression analysis

T. Kanade, Ying-li Tian, J. Cohn
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引用次数: 2809

Abstract

Within the past decade, significant effort has occurred in developing methods of facial expression analysis. Because most investigators have used relatively limited data sets, the generalizability of these various methods remains unknown. We describe the problem space for facial expression analysis, which includes level of description, transitions among expressions, eliciting conditions, reliability and validity of training and test data, individual differences in subjects, head orientation and scene complexity image characteristics, and relation to non-verbal behavior. We then present the CMU-Pittsburgh AU-Coded Face Expression Image Database, which currently includes 2105 digitized image sequences from 182 adult subjects of varying ethnicity, performing multiple tokens of most primary FACS action units. This database is the most comprehensive testbed to date for comparative studies of facial expression analysis.
面部表情分析综合数据库
在过去的十年里,人们在开发面部表情分析方法方面做出了巨大的努力。由于大多数研究人员使用的数据集相对有限,这些不同方法的普遍性仍然未知。我们描述了面部表情分析的问题空间,包括描述水平、表情之间的转换、引出条件、训练和测试数据的信度和效度、受试者的个体差异、头部方向和场景复杂性、图像特征以及与非语言行为的关系。然后,我们提出了CMU-Pittsburgh au编码的面部表情图像数据库,该数据库目前包括来自182个不同种族的成人受试者的2105个数字化图像序列,执行了大多数主要FACS动作单元的多个标记。这个数据库是迄今为止最全面的面部表情分析比较研究的试验台。
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