TY - JOUR
T1 - Preferred spatial frequencies for human face processing are associated with optimal class discrimination in the machine
AU - Keil, Matthias S.
AU - Lapedriza, Agata
AU - Masip, David
AU - Vitria, Jordi
PY - 2008/7/2
Y1 - 2008/7/2
N2 - Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychosical found frequencies. Our results therefore support the notion that the critical band of spatia frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performace. © 2008 Keil et al.
AB - Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychosical found frequencies. Our results therefore support the notion that the critical band of spatia frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performace. © 2008 Keil et al.
U2 - 10.1371/journal.pone.0002590
DO - 10.1371/journal.pone.0002590
M3 - Article
VL - 3
JO - PLoS ONE
JF - PLoS ONE
SN - 1932-6203
IS - 7
M1 - e2590
ER -