TY - GEN
T1 - Combination of fisher scores and appearance based features for face recognition
AU - Chen, Ling
AU - Man, Hong
N1 - Publisher Copyright:
Copyright 2003 ACM.
PY - 2003/11/8
Y1 - 2003/11/8
N2 - A novel feature generation scheme which combines multi-class mapping of Fisher scores and appearance based features for face recognition (FR) is proposed in this paper. Multi-class mapping of Fisher scores is based on partial derivative analysis of parameters of hidden Markov model (HMM), and appearance based features are obtained directed from face images. Linear discriminant analysis (LDA) is used to analyze the feature vectors generated under this scheme. Recognition performance improvement is observed over stand-alone HMM method as well as Fisherface method, which also uses appearance based feature vectors. Moreover, by reducing the number of models involved in the training and testing stages, the proposed feature generation scheme can maintain very high discriminative power at much lower computational complexity comparing to that of the traditional HMM based FR system. Experimental results are provided to demonstrate the viability of this scheme for face recognition.
AB - A novel feature generation scheme which combines multi-class mapping of Fisher scores and appearance based features for face recognition (FR) is proposed in this paper. Multi-class mapping of Fisher scores is based on partial derivative analysis of parameters of hidden Markov model (HMM), and appearance based features are obtained directed from face images. Linear discriminant analysis (LDA) is used to analyze the feature vectors generated under this scheme. Recognition performance improvement is observed over stand-alone HMM method as well as Fisherface method, which also uses appearance based feature vectors. Moreover, by reducing the number of models involved in the training and testing stages, the proposed feature generation scheme can maintain very high discriminative power at much lower computational complexity comparing to that of the traditional HMM based FR system. Experimental results are provided to demonstrate the viability of this scheme for face recognition.
KW - Fisher score
KW - Hidden Markov model
KW - Linear discriminant analysis
UR - http://www.scopus.com/inward/record.url?scp=67649408379&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=67649408379&partnerID=8YFLogxK
U2 - 10.1145/982507.982522
DO - 10.1145/982507.982522
M3 - Conference contribution
AN - SCOPUS:67649408379
T3 - Proceedings of the 2003 ACM SIGMM Workshop on Biometrics Methods and Applications, WBMA 2003
SP - 74
EP - 81
BT - Proceedings of the 2003 ACM SIGMM Workshop on Biometrics Methods and Applications, WBMA 2003
T2 - 2003 ACM SIGMM Workshop on Biometrics Methods and Applications, WBMA 2003
Y2 - 8 November 2003
ER -