A fast feature extraction method

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

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference 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 languageEnglish
Title of host publication2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, proceedings
Pages1797-1800
Number of pages4
DOIs
Publication statusPublished - 29 Sept 2009
EventIEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 - Taipei, Taiwan
Duration: 19 Apr 200924 Apr 2009

Publication series

NameIEEE Conference Publications
PublisherIEEE
ISSN (Electronic)1520-6149

Conference

ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
Country/TerritoryTaiwan
CityTaipei
Period19/04/0924/04/09

Keywords

  • fast Haar transform
  • feature extraction
  • integral vector
  • subspace analysis

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