On the existence of face quality measures

Author

Phillips, Jonathon ; Beveridge, J. Ross ; Bolme, David S. ; Draper, Bruce A. ; Givens, Geof H. ; Yui Man Lui ; Su Cheng ; Teli, Mohammad Nayeem ; Hao Zhang

fYear

2013

fDate

Sept. 29 2013-Oct. 2 2013

Firstpage

1

Lastpage

8

Abstract

We investigate the existence of quality measures for face recognition. First, we introduce the concept of an oracle for image quality in the context of face recognition. Next we introduce greedy pruned ordering (GPO) as an approximation to an image quality oracle. GPO analysis provides an estimated upper bound for quality measures, given a face recognition algorithm and data set. We then assess the performance of 12 commonly proposed face image quality measures against this standard. In addition, we investigate the potential for learning new quality measures via supervised learning. Finally, we show that GPO analysis is applicable to other biometrics.

Keywords

approximation theory; face recognition; greedy algorithms; GPO analysis; biometrics; data set; face image quality measures; face recognition algorithm; greedy pruned ordering; image quality oracle; supervised learning; Algorithm design and analysis; Cameras; Face; Face recognition; Image quality; Support vector machines; Upper bound;

fLanguage

English

Publisher

ieee

Conference_Titel

Biometrics: Theory, Applications and Systems (BTAS), 2013 IEEE Sixth International Conference on

Conference_Location

Arlington, VA

Type

conf

DOI

10.1109/BTAS.2013.6712715

Filename

6712715