A Novel Multi-User Face Detection under Infrared Illumination by Real Adaboost

Location and tracking the human faces is one of the critical technologies in free stereoscopic display system. But because of illumination variation or facial expression, it is difficult to detect human faces accurately and fast. In this paper, an infrared face detection based on real Adaboost algorithm and Cascade structure is implemented. With active infrared illumination, the problem caused by variation of illumination is almost solved, which makes the detection system more robust. Meanwhile, the combination of real Adaboost and Cascade structure pays more attention to the human faces which is more difficult to identify, making the detection quicker a lot. In the detection of video sequence, all human faces can be detected, and misdetection rarely appears. The average processing time on a windows XP, PIV 2.4 GHz PC is about 40 ms for a 640*480-pixel image. So the improved detection is real-time. In addition, experiment proves that the improved detection behaves better when there is variation of facial expression or a little degree leaning of human face. Obviously, the improved detection is more efficient and could be used widely.