Ecse-529a Image Processing and Communication Project Report an Analysis of Eigenfaces for Face Detection Ecse-529a Image Processing and Communication an Analysis of Eigenfaces for Face Detection
نویسندگان
چکیده
ii ABSTRACT This report studies the 1991 Mathew Turk and Alexander Pentland paper: " Face Recognition using Eigenfaces " that appeared in the CVPR proceedings [1]. It has since become an extremely popular approach to face detection. Once implemented, the algorithm proves many of Turk and Pentland's claims of the Eigenface approach to detecting faces with a limited amount of training required. The system proves to be quick and robust while detecting faces of trained and untrained images. Nevertheless, this report delves further and investigates the extents to which Eigenfaces can be used for face detection. Moreover, it examines how different factors (such as intensity, rotation, the size of the training set) may influence the results and the approach's total accuracy. Further, a fundamental flaw in the Turk and Pentland's method of Eigenfaces is revealed.
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