Face Recognition: A Critical Look at Biologically-Inspired Approaches
Gita Sukthankar · 2000
This paper analyzes the merits of two biologically-inspired face recognition models, eigenfaces and graphmatching, 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. For both neuroscientists and computer scientists, face recognition is a fascinating problem with important commercial applications such as mug shot matching, crowd surveillance, and witness face reconstruction. Physiological evidence indicates that the brain possesses specialized face recognition hardware in the form of face detector cells in the inferotemporal cortex and regions in the frontal right hemisphere; impairment in