Combining Template-based and Feature-based Face Detectors

R. Cappelli, A. Franco, D. Maltoni, and L. Nanni (Italy)


Face detection, template matching, multiple-classifiers,Fisher classifier, One-Class SVM.


In this work we present the preliminary results of a face detection system based on an hybrid approach: it combines typical feature-based techniques with image-based analysis, in order to better exploit the main characteristics available in the input image. Different modules contribute to the face detection task: 1) a template-based approach initially proposed in [9], 2) an image-based analysis specifically designed to discard false positives, and 3) multiple-classifiers specifically designed to detect faces. The experimental results show that the new approach is able to achieve an accuracy better than previously reported on a face database with complex backgrounds.

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