Fast gender recognition by using a shared-integral-image approach

Abstract

We develop a new approach for gender recognition. In this paper, our approach uses the rectangle feature vector (RFV) as a representation to identify humans' gender from their faces. The RFV is computationally fast and effective to encode intensity variations of local regions of human face. By only using few rectangle features learned by AdaBoost, we… (More)
DOI: 10.1109/ICASSP.2009.4959635

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