Human and machine recognition of faces: a survey
Chellappa, R.; Wilson, C.L.; Sirohey, S.
Proceedings of the IEEE
Volume 83, Issue 5, May 1995 Page(s):705 - 741
Digital Object Identifier 10.1109/5.381842
Summary:The goal of this paper is to present a critical survey of existing
literature on human and machine recognition of faces. Machine
recognition of faces has several applications, ranging from static
matching of controlled photographs as in mug shots matching and credit
card verification to surveillance video images. Such applications have
different constraints in terms of complexity of processing requirements
and thus present a wide range of different technical challenges. Over
the last 20 years researchers in psychophysics, neural sciences and
engineering, image processing analysis and computer vision have
investigated a number of issues related to face recognition by humans
and machines. Ongoing research activities have been given a renewed
emphasis over the last five years. Existing techniques and systems have
been tested on different sets of images of varying complexities. But
very little synergism exists between studies in psychophysics and the
engineering literature. Most importantly, there exists no evaluation or
benchmarking studies using large databases with the image quality that
arises in commercial and law enforcement applications In this paper, we
first present different applications of face recognition in commercial
and law enforcement sectors. This is followed by a brief overview of the
literature on face recognition in the psychophysics community. We then
present a detailed overview of move than 20 years of research done in
the engineering community. Techniques for segmentation/location of the
face, feature extraction and recognition are reviewed. Global transform
and feature based methods using statistical, structural and neural
classifiers are summarized
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