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@article{1090326, author = {Popovici, Vlad and Thiran, JP}, article_location = {BERLIN}, language = {eng}, issn = {0302-9743}, journal = {AUDIO-AND VIDEO-BASED BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS}, title = {Face detection using an SVM trained in eigenfaces space}, volume = {2688}, year = {2003} }
TY - JOUR ID - 1090326 AU - Popovici, Vlad - Thiran, JP PY - 2003 TI - Face detection using an SVM trained in eigenfaces space JF - AUDIO-AND VIDEO-BASED BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS VL - 2688 SP - 190-198 EP - 190-198 PB - SPRINGER-VERLAG BERLIN SN - 03029743 N2 - The central problem in the case of face detectors is to build a face class model. We present a method for face class modeling in the eigenfaces space using a large-margin classifier like SVM. Two main issues are addressed: what is the required number of eigenfaces to achieve a good classification rate and how to train the SVM for a good generalization. As the experimental evidence show, generally one needs less eigenfaces than usually considered. We will present different strategies for choosing the dimensionality of the PCA space and discuss their effectiveness in the case of face-class modeling. ER -
POPOVICI, Vlad a JP THIRAN. Face detection using an SVM trained in eigenfaces space. \textit{AUDIO-AND VIDEO-BASED BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS}. BERLIN: SPRINGER-VERLAG BERLIN, 2003, roč.~2688, s.~190-198. ISSN~0302-9743.
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