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We describe a new hierarchical face detection algorithm which allows fast background rejection in major parts of images and fine processing in area containing faces. This coarse-to-fine classification strategy is based on learning support vector classifiers (SVMs) with increasing evaluation complexity (resp. decreasing invariance and false alarm rates) top-down in the hierarchy. The complexity, in terms of the number of support vectors, of each detector in the hierarchy is reduced bydoi:10.1109/icpr.2002.1047868 dblp:conf/icpr/SahbiB02 fatcat:hnuoki337re7tb7n6p4ubcpynm