Experimental Analysis of Classification of Facial Images

Autor:	S. D. Sapkal, M. D. Malkauthekar, S. N. Kakarwal
Rok vydání:	2009
Předmět:	FERET database Contextual image classification business.industry Computer science Fisher kernel Pattern recognition Similarity measure Linear discriminant analysis Facial recognition system Euclidean distance Face (geometry) Computer vision Artificial intelligence business
Zdroj:	2009 IEEE International Advance Computing Conference.
DOI:	10.1109/iadcc.2009.4809166
Popis:	This paper proposes a face recognition method using the FERET face database. Facial images of two classes and three classes with different expressions and angles are used for classification. Fisher Discriminant Method is used for comparison of the results of two classes with the results of three classes. Euclidian distance method is used for similarity measure. The experimental results have been demonstrated that performance of Fisher Discriminant Analysis for three classes is same as the performance for two classes[1].
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a3e80461df5ba740602c30b7bb48fdc9 https://doi.org/10.1109/iadcc.2009.4809166 Zobrazit plný text záznamu