Forensic Face Recognition: A Survey


Ali, Tauseef and Spreeuwers, Luuk and Veldhuis, Raymond (2012) Forensic Face Recognition: A Survey. In: Adamo Quaglia & Calogera M. Epifano (Eds.), Face Recognition: Methods, Applications and Technology. Computer Science, Technology and Applications . Nova Publishers, pp. 1-19. ISBN 9781619426634

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Abstract:The improvements of automatic face recognition during the last 2 decades have disclosed new applications like border control and camera surveillance. A new application field is forensic face recognition. Traditionally, face recognition by human experts has been used in forensics, but now there is a quickly developing interest in automatic face recognition as well. At the same time there is a trend towards a more objective and quantitative approach for traditional manual face comparison by human experts. Unlike in most applications of face recognition, in the forensic domain a binary decision or a score does not suffice as a result to be used in court. Rather, in the forensic domain, the outcome of the recognition process should be in the form of evidence or support for a prosecution hypothesis verses a defence hypothesis. In addition, in the forensic domain, trace images are often of poor quality. The available literature on (automatic) forensic face recognition is still very limited. In this survey, an overview is given of the characteristics of forensic face recognition and the main publications. The survey introduces forensic face recognition and reports on attempts to use automatic face recognition in the forensic context. Forensic facial comparison by human experts and the development of guidelines and a more quantitative and objective approach are also addressed. Probably the most important topic of the survey is the development of a framework to use automatic face recognition in the forensic setting. The Bayesian framework is a logical choice and likelihood ratios can in principle be used directly in court. In the statistical evaluation of the trace image, the choice of databases of facial images plays a very important role.
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Electrical Engineering, Mathematics and Computer Science (EEMCS)
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