Two-stage classification using selective attention for fast face detection

Author

Jones, Steve R. ; Capson, David W.

Author_Institution

Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada

Volume

5

fYear

2005

fDate

18-23 March 2005

Abstract

A novel system for face detection in images and video sequences is presented. The system incorporates a two-stage linear discriminant and nonlinear support vector machine classifier coupled with a front-end biologically-inspired search scheme. Results based on the CMU test set demonstrate that by using such a classifier arrangement with a non-exhaustive searching scheme, a significant reduction in computational complexity is achieved while maintaining comparable accuracy to other leading face detection systems.

Keywords

face recognition; image classification; support vector machines; biologically-inspired search scheme; fast face detection; front-end selective attention system; linear discriminant classifier; nonexhaustive searching scheme; nonlinear support vector machine classifier; two-stage classification; Detectors; Face detection; Face recognition; Neural networks; Risk management; Statistical learning; Support vector machine classification; Support vector machines; Testing; Video sequences;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on

ISSN

1520-6149

Print_ISBN

0-7803-8874-7

Type

conf

DOI

10.1109/ICASSP.2005.1416341

Filename

1416341