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Published Articles >> Table of Contents >> Abstract
IEEE International Workshop on Analysis and Modeling of Faces and Gestures
p. 5
Discriminant Analysis of Stochastic Models and Its Application to Face Recognition
Ling Chen, Stevens Institute of Technology
Hong Man, Stevens Institute of Technology
Full Article Text:
  
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AMFG.2003.1240817
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| Abstract |
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As the vital component of a recently developed
stochastic model based feature generation scheme, Fisher score
is increasingly used in classification applications. In this work we
present a generalization of previous proposed feature generation
schemes by introducing the concept of multi-class mapping which
is oriented to multi-class classification problems. Based on the
generalized feature generation scheme, a novel face recognition
system is developed by a systematical integration of hidden
Markov model (HMM) and linear discriminant analysis (LDA).
The proposed system is evaluated on a public available face
database of 50 subjects. Comparing to holistic features based
LDA method, stand alone HMM method, and LDA method based
on previous proposed feature generation schemes which are intrinsically
oriented to two-class problems, superior performance
is obtained by our method in terms of recognition accuracy.
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 Additional Information
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Citation:
Ling Chen, Hong Man,
"Discriminant Analysis of Stochastic Models and Its Application to Face Recognition,"
amfg,
p. 5,
IEEE International Workshop on Analysis and Modeling of Faces and Gestures,
2003
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