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Beumer, G.M.
(2009)
Face recognition, a landmarks tale.
PhD thesis, University of Twente.
ISBN 978-90-365-2891-7
Full text available as:
Official URL: http://dx.doi.org/10.3990/1.9789036528917  AbstractFace recognition is a technology that appeals to the imagination of many people. This is particularly reflected in the popularity of science-fiction films and forensic detective series such as CSI, CSI New York, CSI Miami, Bones and NCIS. Although these series tend to be set in the present, their application of face recognition should be considered science-fiction. The successes are not, or at least not yet, realistic. This does, however, not mean that it does not, or will never, work. To the contrary, face recognition is used in places where the user does not need or want to cooperate, for example entry to stadiums or stations, or the detection of double entries into databases. Another important reason to use face recognition is that it can be a user-friendly biometric security. Face recognition works reliably and robustly when there is little variance in pose in the images used. In order to eliminate variance, the faces are aligned to a reference. For this we will use a set of landmarks. Landmarks are points which are easy recognisable locations on the face such as the eyes, nose and mouth. A probabilistic, maximum a posteriori approach to finding landmarks in a facial image is proposed, which provides a theoretical framework for template based landmarkers. One such landmarker, based on a likelihood ratio detector, is discussed in detail. Special attention is paid to training and implementation issues, in order to minimize storage and processing requirements. In particular, a fast approximate singular value decomposition method is proposed to speed up the training process and an implementation of the landmarker in the Fourier domain is presented that will speed up the search process. A subspace method for outlier correction and an alternative implementation of the landmarker are shown to improve its accuracy. The impact of carefully tuning the many parameters of the method is shown. The method is extensively tested and compared with alternatives. Although state of the art face recognition still has a giant leap to make, before it is as good as on television, small steps are made by men all the time.
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