Abstract
Advancement in computer technology has made possible to evoke new video processing applications in field of biometric recognition. Applications include face detection and recognition integrated to surveillance systems, gesture analysis etc. The first step in any face analysis systems is near real-time detection of face in sequential frames containing face and complex objects in background. In this paper a system is proposed for human face detection and recognition in videos. Efforts are made to minimize processing time for detection and recognition process. To reduce human intervention and increase overall system efficiency the system is segregated into three stages- motion detection, face detection and recognition. Motion detection reduces the search area and processing complexity of systems. Face detection is achieved in near real-time with use of haar features and recognition using gabor feature matching.
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