Face Recognition (2007)

Description

Face recognition is a task humans perform remarkably easily and successfully. This apparent simplicity was shown to be dangerously misleading as the automatic face recognition seems to be a problem that is still far from solved. In spite of more than 20 years of extensive research, large number of papers published in journals and conferences dedicated to this area, we still can not claim that artificial systems can measure to human performance.

Automatic face recognition is intricate primarily because of difficult imaging conditions (lighting and viewpoint changes induced by body movement) and because of various other effects like aging, facial expressions, occlusions etc. Researchers from computer vision, image analysis and processing, pattern recognition, machine learning and other areas are working jointly, motivated largely by a number of possible practical applications. The goal of this book is to give a clear picture of the current state-of-the-art in the field of automatic face recognition across three main areas of interest: biometrics, cognitive models and human-computer interaction. Face recognition has an important advantage over other biometric technologies - it is a nonintrusive and easy to use method. As such, it became one of three identification methods used in e-passports and a biometric of choice for many other security applications. Cognitive and perception models constitute an important platform for interdisciplinary research, connecting scientists from seemingly incompatible areas and enabling them to exchange methodologies and results on a common problem. Evidence from neurobiological, psychological, perceptual and cognitive experiments provide potentially useful insights into how our visual system codes, stores and recognizes faces. These insights can then be connected to artificial solutions. On the other hand, it is generally believed that the success or failure of automatic face recognition systems might inform cognitive and perception science community about which models have the potential to be candidates for those used by humans. Making robots and computers more "human" (through human-computer interaction) will improve the quality of human-robot co-existence in the same space and thus alleviate their adoption into our every day lives. In order to achieve this, robots must be able to identify faces, expressions and emotions while interacting with humans.



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