DocumentCode
2410618
Title
An evaluation of face and ear biometrics
Author
Victor, Barnabas ; Bowyer, Kevin ; Sarka, Sudeep
Author_Institution
Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA
Volume
1
fYear
2002
fDate
2002
Firstpage
429
Abstract
Face recognition based on principal component analysis is a heavily researched topic in computer vision. The ear has been proposed as a biometric, with claimed advantages over the face. We have applied the PCA approach to images of the face and ear using the same set of subjects. Testing was done with three different gallery/probe combinations. For faces we have: 1) probes of same day but different expression, 2) probes of a different day but similar expression, and 3) probes of different day and different expression. Analogously, for ears, we have: 1) probes of same day but other ear, 2) probes of a different day but same ear, and 3) probes of different day and other ear Results indicate that the face provides a more reliable biometric than the ear.
Keywords
computer vision; eigenvalues and eigenfunctions; face recognition; principal component analysis; computer vision; ear biometrics; face biometrics; face recognition; principal component analysis; Biometrics; Computer vision; Ear; Face detection; Face recognition; Lighting; Pixel; Principal component analysis; Probes; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2002. Proceedings. 16th International Conference on
ISSN
1051-4651
Print_ISBN
0-7695-1695-X
Type
conf
DOI
10.1109/ICPR.2002.1044746
Filename
1044746
Link To Document