A fast feature extraction method

Author

Pan, Jing ; Yanwei Pang ; Li, Xuelong ; Yuan, Yuan ; Tao, Dacheng

Author_Institution

Electron. Eng. Dept., Tianjin Univ. of Technol. & Educ., Tianjin

fYear

2009

fDate

19-24 April 2009

Firstpage

1797

Lastpage

1800

Abstract

A fast subspace analysis and feature extraction algorithm is proposed which is based on fast Haar transform and integral vector. In rapid object detection and conventional binary subspace learning, Haar-like functions have been frequently used but true Haar functions are seldom employed. In this paper we have shown that true Haar functions can be successfully used to accelerate subspace analysis and feature extraction. Both the training and testing speed of the proposed method is higher than conventional algorithms. Experimental results on face database demonstrated its effectiveness.

Keywords

Haar transforms; feature extraction; learning (artificial intelligence); object detection; Haar-like functions; conventional binary subspace learning; face database; fast Haar transform; fast feature extraction method; fast subspace analysis; integral vector; object detection; Algorithm design and analysis; Computational efficiency; Computer science education; Computer vision; Data mining; Educational institutions; Educational technology; Feature extraction; Image storage; Iterative algorithms; Feature extraction; fast Haar transform; integral vector; subspace analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on

Conference_Location

Taipei

ISSN

1520-6149

Print_ISBN

978-1-4244-2353-8

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2009.4959954

Filename

4959954