DocumentCode :
2337512
Title :
A novel method of recognizing ageing face based on EHMM
Author :
Sun, Ye ; Zhang, Jian-Ming ; Wang, Liang-Min ; Zhan, Yong-Zhao ; Song, Shun-Lin
Author_Institution :
Sch. of Comput. Sci. & Telecommun. Eng., Jiangsu Univ., China
Volume :
8
fYear :
2005
fDate :
18-21 Aug. 2005
Firstpage :
4599
Abstract :
The existing automatic methods of face recognition cannot recognize ageing faces with great changes in facial appearance. In this paper, a novel algorithm based on EHMM (embedded hidden Markov model) is presented to recognize the face with large ageing effects. Firstly, the non-linear relations between age and motions of key feature points in face are achieved by analyzing a great number of samples, and then a non-linear model is built to describe these relations. Secondly, together with PARI (partial ageing ratio image), texture of the ageing faces is predicted. Thirdly, features extracted from reconstructed images are used to train EHMM and face recognition is performed in the test set, where faces are in large age span. Experimental result shows that the algorithm proposed outperformed the traditional EHMM method.
Keywords :
face recognition; feature extraction; hidden Markov models; image reconstruction; image sampling; image texture; learning (artificial intelligence); EHMM; ageing face recognition; ageing face texture; embedded hidden Markov model; feature extraction; image reconstruction; partial ageing ratio image; Aging; Computer science; Face recognition; Hidden Markov models; Motion analysis; Polynomials; Reconstruction algorithms; Shape; Sun; Testing; Ageing face; EHMM; ageing prediction; face recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
Type :
conf
DOI :
10.1109/ICMLC.2005.1527749
Filename :
1527749
Link To Document :
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