Face Recognition Using Markov Stationary Features and Vector Quantization Histogram

Author

Qiu Chen ; Kotani, Koji ; Feifei Lee ; Ohmi, Tadahiro

Author_Institution

Dept. of Inf. & Commun. Eng., Kogakuin Univ., Tokyo, Japan

fYear

2014

fDate

19-21 Dec. 2014

Firstpage

1934

Lastpage

1938

Abstract

We have proposed a very simple yet highly reliable face recognition algorithm using VQ histogram. This histogram, obtained by Vector Quantization (VQ) processing for the facial image, is utilized as a very effective personal feature. In this paper, we combine the VQ histogram with Markov Stationary Features (MSF) so as to add spatial structure information to histogram. Experimental results show maximum average recognition rate of 96.16% is obtained for 400 images of 40 persons from the publicly available face database of AT&T Laboratories Cambridge.

Keywords

Markov processes; face recognition; vector quantisation; visual databases; AT&T Laboratories Cambridge; MSF; Markov stationary features; VQ histogram; face recognition algorithm; maximum average recognition rate; personal feature; publicly available face database; spatial structure information; vector quantization histogram; Databases; Face; Face recognition; Histograms; Image recognition; Markov processes; Vector quantization; Face recognition; Histogram feature; Markov stationary features (MSF); Vector quantization (VQ);

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4799-7980-6

Type

conf

DOI

10.1109/CSE.2014.354

Filename

7023866