Decreasing Volume of Face Images Database and Efficient Face Detection Algorithm

摘要

As one of the most successful applications of image analysis and understanding, face recognition hasrecently gained significant attention. Over the last ten years or so, it has become a popular area of research incomputer vision and one of the most successful applications of image analysis and understanding. A facialrecognition system is a computer application for automatically identifying or verifying a person from a digitalimage or a video frame from a video source. One of the ways to do this is by comparing selected facial featuresfrom the image and a facial database. Biometric face recognition, otherwise known as Automatic FaceRecognition (AFR), is a particularly attractive biometric approach, since it focuses on the same identifier thathumans use primarily to distinguish one person from another: their “faces”. One of its main goals is theunderstanding of the complex human visual system and the knowledge of how humans represent faces in orderto discriminate different identities with high accuracy.Human face and facial feature detection have attracted a lot of attention because of their wide applications, suchas face recognition, face image database management and human-computer interaction. So it is of interest todevelop a fast and robust algorithm to detect the human face and facial features. This paper describes a visualobject detection framework that is capable of processing images extremely rapidly while achieving high detectionrates.