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GMM-based SVM for face recognition

9 years 11 months ago
GMM-based SVM for face recognition
A new face recognition algorithm is presented. It supposes that a video sequence of a person is available both at enrollment and test time. During enrollment, a client Gaussian Mixture Model (GMM) is adapted from a world GMM using eigenface features extracted from each frame of the video. Then, a Support Vector Machine (SVM) is used to find a decision border between the client GMM and pseudoimpostors GMMs. At test time, a GMM is adapted from the test video and a decision is taken using the previously learned client SVM. This algorithm brings a 3.5% Equal Error Rate (EER) improvement over the BioSecure reference system on the Pooled protocol of the BANCA database.
Gérard Chollet, Hervé Bredin, Najim
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2006
Where ICPR
Authors Gérard Chollet, Hervé Bredin, Najim Dehak
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