Ensemble SVM Regression Based Multi-View Face Detection System

In this paper, we present a novel learning method for SVM (Support Vector Machine) regression ensemble used in multi-pose face detection. Firstly, several view-specific SVM classifiers are trained by using corresponding positive and negative examples. And then, an ensemble mechanism (SVM regression) is used to combine the results from the view-specific SVCs (Support Vector Classifiers). Experimental results show that the detection accuracy of the ensemble is better than the view-specific SVCs. Moreover, the SVR ensemble does not need extra pose estimation process prior to the classification; it generates pose information in addition to its detection results.