Real-time gender classification
Bo Wu, Haizhou Ai, Chang Huang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
This paper introduces an automatic real-time gender classification system. The system consists of mainly three modules, face detection, normalization and gender classification. The LUT-type weak classifier based on Adaboost learning method is proposed for training both face detector and gender classifier, and a Simple Direct Appearance Model (SDAM) based method is developed to detect the facial landmark points for face normalization. This results in an integrated system with rather good performance. Experiment results on both pictures from World Wide Web and real-time video clips are reported to demonstrate its effectiveness and robustness.