Face Recognition: A Critical Look at Biologically-Inspired Approaches
Tech. Report, CMU-RI-TR-00-04, Robotics Institute, Carnegie Mellon University, 2000
Abstract
This paper analyzes the merits of two biologically-inspired face recognition models, eigenfaces and graph-matching, in the context of related neurophysiological and psychophysical data. Given the ambiguity of current biological evidence, a more promising direction for future face recognition research is in the development of models that conform more closely to human perception of facial similarity.
BibTeX
@techreport{Sukthankar-2000-7964,author = {Gita Sukthankar},
title = {Face Recognition: A Critical Look at Biologically-Inspired Approaches},
year = {2000},
month = {January},
institute = {Carnegie Mellon University},
address = {Pittsburgh, PA},
number = {CMU-RI-TR-00-04},
keywords = {vision, face recognition, biological modeling},
}
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