A fast feature extraction method

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

doi:10.1109/ICASSP.2009.4959954

A fast feature extraction method

Jing Pan^*, Yanwei Pang, Xuelong Li, Yuan Yuan, Dacheng Tao

^*Corresponding author for this work

Computer Science Research Group

Research output: Chapter in Book/Published conference output › Conference publication

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.

Original language	English
Title of host publication	2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, proceedings
Pages	1797-1800
Number of pages	4
DOIs	https://doi.org/10.1109/ICASSP.2009.4959954
Publication status	Published - 29 Sept 2009
Event	IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 - Taipei, Taiwan Duration: 19 Apr 2009 → 24 Apr 2009

Publication series

Name	IEEE Conference Publications
Publisher	IEEE
ISSN (Electronic)	1520-6149

Conference

Conference	IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
Country/Territory	Taiwan
City	Taipei
Period	19/04/09 → 24/04/09

Keywords

fast Haar transform
feature extraction
integral vector
subspace analysis

Access to Document

10.1109/ICASSP.2009.4959954

Cite this

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title = "A fast feature extraction method",

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 = "fast Haar transform, feature extraction, integral vector, subspace analysis",

author = "Jing Pan and Yanwei Pang and Xuelong Li and Yuan Yuan and Dacheng Tao",

year = "2009",

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language = "English",

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series = "IEEE Conference Publications",

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note = "IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 ; Conference date: 19-04-2009 Through 24-04-2009",

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Pan, J, Pang, Y, Li, X, Yuan, Y & Tao, D 2009, A fast feature extraction method. in 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, proceedings. IEEE Conference Publications, pp. 1797-1800, IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009, Taipei, Taiwan, 19/04/09. https://doi.org/10.1109/ICASSP.2009.4959954

TY - GEN

T1 - A fast feature extraction method

AU - Pan, Jing

AU - Pang, Yanwei

AU - Li, Xuelong

AU - Yuan, Yuan

AU - Tao, Dacheng

PY - 2009/9/29

Y1 - 2009/9/29

N2 - 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.

AB - 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.

KW - fast Haar transform

KW - feature extraction

KW - integral vector

KW - subspace analysis

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UR - http://ieeexplore.ieee.org/document/4959954/

U2 - 10.1109/ICASSP.2009.4959954

DO - 10.1109/ICASSP.2009.4959954

M3 - Conference publication

AN - SCOPUS:69749122795

SN - 978-1-4244-2354-5

T3 - IEEE Conference Publications

SP - 1797

EP - 1800

BT - 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, proceedings

T2 - IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009

Y2 - 19 April 2009 through 24 April 2009

ER -

A fast feature extraction method

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