Simple 1D Discrete Hidden Markov Models for face recognition

被引：0
|
作者：
Le, HS [1 ]
Li, HB [1 ]
机构：
[1] Umea Univ, Dept Appl Phys & Elect, Digital Media Lab, SE-90187 Umea, Sweden
来源：
VISUAL CONTENT PROCESSING AND REPRESENTATION, PROCEEDINGS | 2003年 / 2849卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We propose an approach to cope with the problem of 2D face image recognition system by using ID Discrete Hidden Markov Model (1D-DHMM). The Haar wavelet transform was applied to the image to lessen the dimension of the observation vectors. The system was tested on the facial database obtained from AT&T Laboratories Cambridge (ORL). Five images of each individuals were used for training, while another five images were used for testing and recognition rate was achieved at 100%, while significantly reduced the computational complexity compared to other 2D-HMM, 2D-PHMM based face recognition systems. The experiments done in Matlab took 1.13 second to train the model for each person, and the recognition time was about 0.3 second.
引用
收藏
页码：41 / 49
页数：9
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