Face detection and recognition in videos

Advancement in computer technology has made possible to evoke new video processing applications in field of biometric face detection and recognition. It has wide range of applications in human recognition, human computer interaction (HCI), behavior analysis, teleconferencing and video surveillance. Face is vital part of human anatomy that reflects prominent topographies of a person. Face detection has become popular biometric trait in recent years due to its importance in security control applications. The first step in practical face analysis systems is real-time detection of face in frames containing face and complex objects in background. In this paper a system is proposed for human face detection using Haar features and recognition using Eigen and Gabor filter in videos. Efforts are made to minimize processing time for detection and recognition process. The Eigenface method performs well in terms of computational complexity whereas Gabor filter are robust to pose changes.