Title :
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
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);
Conference_Titel :
Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4799-7980-6
DOI :
10.1109/CSE.2014.354