Ensemble SVM Regression Based Multi-View Face Detection System

In this paper, we present a novel learning method for SVM regression ensemble used in multi-pose face detection. Firstly, several view-specific SVM classifiers are trained using corresponding positive and negative examples. Then an ensemble mechanism (SVM regression) is trained to combine the results from the view-specific SVCs. 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 result.