Title :
On the Dimensionality of Face Space
Author :
Meytlis, Marsha ; Sirovich, Lawrence
Author_Institution :
Mount Sinai Sch. of Med., New York
fDate :
7/1/2007 12:00:00 AM
Abstract :
The dimensionality of face space is measured objectively in a psychophysical study. Within this framework, we obtain a measurement of the dimension for the human visual system. Using an eigenface basis, evidence is presented that talented human observers are able to identify familiar faces that lie in a space of roughly 100 dimensions and the average observer requires a space of between 100 and 200 dimensions. This is below most current estimates. It is further argued that these estimates give an upper bound for face space dimension and this might be lowered by better constructed "eigenfaces" and by talented observers.
Keywords :
face recognition; image classification; statistical analysis; visual perception; eigenface; face classification; face recognition problem; face space dimensionality measure; familiar face identification; human visual system; talented human observers; Databases; Eigenvalues and eigenfunctions; Extraterrestrial measurements; Face detection; Face recognition; Humans; Image recognition; Psychology; Testing; Visual system; Face and gesture recognition; computational models of vision; psychology; singular value decomposition.; Algorithms; Artificial Intelligence; Biometry; Face; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2007.1033