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JOINT AMI/PASCAL/IM2/M4 Workshop on Multimodal Interaction and Related Machine Learning Algorithms

Mixture of SVMs for Face Class Modeling

author: Julien Meynet, Signal Processing Institute

Description

We 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 real-time 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 {SVMa}. 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.

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Slides
0:01 Mixture of SVMs for Face Class Modeling
0:15 Outline
0:58 Face Detection Methods
1:59 Principle of the detection
2:49 Eigenfaces Space
3:46 Distance From Feature Space
4:25 Support Vector Machines (SVM)
5:44 Mixture of SVMs (MSVM)
7:08 Mixture of SVMs
8:19 Mixture of SVMs
8:59 Experiments and Results I
10:14 Experiments and Results II
11:36 Experiments and Results III
13:04 Conclusions - Future Work

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Reviews and comments:

Comment1 Mehmet, April 26, 2008 at 4:38 p.m.:

Good presentation. I appreciate it.

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