Video-based face recognition using a probabilistic graphical model

Yi Chia Chan, Cheng Chieh Chiang, Kai Ming Wang, Greg C. Lee

研究成果: 書貢獻/報告類型會議論文篇章

摘要

This paper presents a probabilistic graphical model to formulate and deal with video-based face recognition. Our formulation divides the problem into two parts: one for likelihood measure and the other for transition measure. The likelihood measure can be regarded as a traditional task of face recognition within a single image, i.e., to recognize who the current observing face image is. In our work, two-dimensional linear discriminant analysis (2DLDA) is employed to judge the likelihood measure. Moreover, the transition measure estimates the probability of the change from a false recognition at the previous stage to the correct person at the current stage. Our approach for transition measure does not only consider the visual difference among persons according to the training face images but also involve prior information of the pose change in video frames. We also provide several experiments to show the efficiency of our proposed approach in this paper.

原文英語
主出版物標題Proceedings of the 11th IAPR Conference on Machine Vision Applications, MVA 2009
頁面106-109
頁數4
出版狀態已發佈 - 2009
事件11th IAPR Conference on Machine Vision Applications, MVA 2009 - Yokohama, 日本
持續時間: 2009 五月 202009 五月 22

出版系列

名字Proceedings of the 11th IAPR Conference on Machine Vision Applications, MVA 2009

其他

其他11th IAPR Conference on Machine Vision Applications, MVA 2009
國家/地區日本
城市Yokohama
期間2009/05/202009/05/22

ASJC Scopus subject areas

  • 電腦視覺和模式識別

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