Discriminant analysis of stochastic models and its application to face recognition

Ling Chen, Hong Man

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationIEEE International Workshop on Analysis and Modeling of Faces and Gestures, AMFG 2003
Pages5-10
Number of pages6
ISBN (Electronic)0769520103, 9780769520100
StatePublished - 2003
Event2003 IEEE International Workshop on Analysis and Modeling of Faces and Gestures, AMFG 2003 - Nice, France
Duration: 17 Oct 2003 → …

Publication series

NameIEEE International Workshop on Analysis and Modeling of Faces and Gestures, AMFG 2003

Conference

Conference2003 IEEE International Workshop on Analysis and Modeling of Faces and Gestures, AMFG 2003
Country/TerritoryFrance
CityNice
Period17/10/03 → …

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