Face class modeling using mixture of SVMs

MEYNET, J; Vlad POPOVICI a JP THIRAN. Face class modeling using mixture of SVMs. IMAGE ANALYSIS AND RECOGNITION, PT 2, PROCEEDINGS. BERLIN: SPRINGER-VERLAG BERLIN, 2004, roč. 3212, s. 709-716. ISSN 0302-9743.

Základní údaje

Originální název

Face class modeling using mixture of SVMs

Autoři

MEYNET, J; Vlad POPOVICI a JP THIRAN

Vydání

IMAGE ANALYSIS AND RECOGNITION, PT 2, PROCEEDINGS, BERLIN, SPRINGER-VERLAG BERLIN, 2004, 0302-9743

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Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Utajení

není předmětem státního či obchodního tajemství

Označené pro přenos do RIV

Ne

UT WoS

000224317200086

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Anotace

V originále

We(1) present a method for face detection which uses a new SVM structure trained in an expert manner in the eigenface space. This robust method has been introduced as a post processing step in a realtime face detection system. The principle is to train several parallel SVMs on subsets of some initial training set and then train a second layer SVM on the margins of the first layer of SVMs. This approach presents a number of advantages over the classical SVM: firstly the training time is considerably reduced and secondly the classification performance is improved, we will present some comparisions with the single SVM approach for the case of human face class modeling.