Face Recognition Method by Using Large and Representative Datasets
A face recognition method by using large and representative datasets is presented in this paper. The importance of research on face recognition is fueled by both its scientific challenges and its potential applications. In this contribution, we proposes several approaches to deal with some of the difficulties that one encounters when trying to recognize frontal faces in unconstrained domains and when only one sample per class is available to the learning system. It is possible for an automatic recognition system to compensate for imprecisely localized, partially expression variant faces even when only one single training sample per class is available. Finally, we have shown that the results of an appearance-based approach totally depend on the differences that exist between the facial expressions displayed on the learning and testing images.
Face Recognition Representative Datasets Principal Component Analysis Pattern Recognition
Zhao Tongzhou Wang Yanli Wang Haihui Gao Sheng Song Hongxian
School of Computer Science & Engineering,Wuhan Institute of Technology,Wuhan,430073,China
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
5059-5062
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）