Facial Recognition

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Author(s): Rory A. Lewis (UNC-Charlotte, USA)and Zbigniew W. Ras (University of North Carolina, Charlotte, USA)
Copyright: 2009
Pages: 6
Source title: Encyclopedia of Data Warehousing and Mining, Second Edition
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-60566-010-3.ch132

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Abstract

Over the past decade Facial Recognition has become more cohesive and reliable than ever before. We begin with an analysis explaining why certain facial recognition methodologies examined under FERET, FRVT 2000, FRVT 2002, and FRVT 2006 have become stronger and why other approaches to facial recognition are losing traction. Second, we cluster the stronger approaches in terms of what approaches are mutually inclusive or exclusive to surrounding methodologies. Third, we discuss and compare emerging facial recognition technology in light of the aforementioned clusters. In conclusion, we suggest a road map that takes into consideration the final goals of each cluster, that given each clusters weakness, will make it easier to combine methodologies with surrounding clusters.

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