DocumentCode
698478
Title
Combining SVMS for face class modeling
Author
Meynet, Julien ; Popovici, Vlad ; Sorci, Matteo ; Thiran, Jean-Philippe
Author_Institution
Signal Process. Inst., Ecole Polytech. Fed. de Lausanne (EPFL), Lausanne, Switzerland
fYear
2005
fDate
4-8 Sept. 2005
Firstpage
1
Lastpage
4
Abstract
We present a method for combining a number of Support Vector Machines trained independently in the eigenface space and we apply it to face class modeling. We first train several SVMs on subsets of some initial training set and then combine their expertise using various probabilistic combining rules. This approach is compared to a classical SVM classification as well as Multiple SVM classification[1].
Keywords
eigenvalues and eigenfunctions; face recognition; image classification; object detection; probability; set theory; support vector machines; SVM; automatic face detection; eigenface space; face analysis; face class modeling; initial training set; probabilistic combining rules; support vector machines; Databases; Face; Face detection; Principal component analysis; Support vector machines; Training; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Conference, 2005 13th European
Conference_Location
Antalya
Print_ISBN
978-160-4238-21-1
Type
conf
Filename
7078063
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