Image Sampling for Invariant Face Recognition

Author

Wang, Jing-Wein ; Chen, Tzu-Hsiung ; Wang, Chia-Nan

Author_Institution

Inst. of Photonics & Commun., Nat. Kaohsiung Univ. of Appl. Sci., Kaohsiung, Taiwan

fYear

2012

fDate

4-6 June 2012

Firstpage

479

Lastpage

482

Abstract

In this paper we present a novel scheme for reducing the impact of variations in head pose on face recognition. As its heavy reliance on the sampling center makes traditional log-polar sampling poorly suited for eliminating the impact of variation in head pose, we successfully overcome this problem using a quincunx pyramid sampling algorithm of our own design. Tests using the faces of 100 subjects from the color FERET database show that the algorithm we propose provides an accurate acceptance rate of 99.8% and a false acceptance rate of 0%.

Keywords

face recognition; image colour analysis; visual databases; accurate acceptance rate; color FERET database; false acceptance rate; head pose variation; heavy reliance; image sampling; invariant face recognition; log polar sampling; quincunx pyramid sampling algorithm; sampling center; Databases; Face; Face recognition; Image color analysis; Principal component analysis; Testing; Face recognition; color FERET database; log-polar sampling; quincunx pyramid sampling;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer, Consumer and Control (IS3C), 2012 International Symposium on

Conference_Location

Taichung

Print_ISBN

978-1-4673-0767-3

Type

conf

DOI

10.1109/IS3C.2012.127

Filename

6228350