Face Class Modeling Using Mixture of SVMs

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.

• Type: Conference
• Year: 2004
• Where: ICIAR
• Authors: Julien Meynet, Vlad Popovici, Jean-Philippe Thiran
• Keywords: Face Detection, ICIAR 2004, Layer Svm, Single Svm Approach