Face recognition using scale invariant feature transform and support vector machine

Lichun Zhang, Junwei Chen, Yue Lu, Patrick Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

23 Scopus citations

Abstract

Face recognition has received significant attention in the last decades for many potential applications. Recently, the Scale Invariant Feature Transform (SIFT) becomes an interesting technique for the task of object recognition. This paper investigated the application of the SIFT approach to the face recognition and proposed a new method based on SIFT and Support Vector Machine (SVM) for the face recognition problem. First the SIFT features are generated and then SVM is used for the classification. The presented method has been tested with the ORL database and the Yale face database, and the recognition results demonstrate its robust performance under different expression conditions.

Original languageEnglish
Title of host publicationProceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008
Pages1766-1770
Number of pages5
DOIs
StatePublished - 2008
Event9th International Conference for Young Computer Scientists, ICYCS 2008 - Zhang Jia Jie, Hunan, China
Duration: 18 Nov 200821 Nov 2008

Publication series

NameProceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008

Conference

Conference9th International Conference for Young Computer Scientists, ICYCS 2008
Country/TerritoryChina
CityZhang Jia Jie, Hunan
Period18/11/0821/11/08

Keywords

  • Face recognition
  • SIFT feature
  • Support vector machine (SVM)

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