The Comparison of Normal Bayes and SVM Classifiers in the Context of Face Shape Recognition

Adam Schmidt

doi:10.1007/978-3-540-93905-4_12

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Title

The Comparison of Normal Bayes and SVM Classifiers in the Context of Face Shape Recognition

Authors

Adam Schmidt (WE) ^{[ 1 ][ P ]}

^{[ 1 ]} Instytut Automatyki i Inżynierii Informatycznej, Wydział Elektryczny, Politechnika Poznańska | ^{[ P ]} employee

Year of publication

2009

Chapter type

chapter in monograph

Publication language

english

Abstract

EN In this paper the face recognition system based on the shape information extracted with the Active Shape Model is presented. Three different classification approaches have been used: the Normal Bayes Classifier, the Type 1 Linear Support Vector Machine (LSVM) and the type 2 LSVM with a soft margin. The influence of the shape extraction algorithm parameters on the classification efficiency has been investigated. The experiments were conducted on a set of 3300 images of 100 people which ensures the statistical significance of the obtained results.

Pages (from - to)

95 - 102

DOI

10.1007/978-3-540-93905-4_12

URL

https://link.springer.com/chapter/10.1007/978-3-540-93905-4_12

Book

Computer Recognition Systems 3

System created by Poznań University of Technology and Poznan Supercomputing and Networking Center

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