Face recognition using scale invariant feature transform and support vector machine

Lichun Zhang; Junwei Chen; Yue Lu; Patrick Wang

doi:10.1109/ICYCS.2008.481

Face recognition using scale invariant feature transform and support vector machine

Lichun Zhang^*
, Junwei Chen
, Yue Lu
, Patrick Wang

^*Corresponding author for this work

School of Communication and Electronic Engineering

East China Normal University
Northeastern University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	Proceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008
Pages	1766-1770
Number of pages	5
DOIs	https://doi.org/10.1109/ICYCS.2008.481
State	Published - 2008
Event	9th International Conference for Young Computer Scientists, ICYCS 2008 - Zhang Jia Jie, Hunan, China Duration: 18 Nov 2008 → 21 Nov 2008

Publication series

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

Conference

Conference	9th International Conference for Young Computer Scientists, ICYCS 2008
Country/Territory	China
City	Zhang Jia Jie, Hunan
Period	18/11/08 → 21/11/08

Keywords

Face recognition
SIFT feature
Support vector machine (SVM)

Access to Document

10.1109/ICYCS.2008.481

Cite this

Zhang, L., Chen, J., Lu, Y., & Wang, P. (2008). Face recognition using scale invariant feature transform and support vector machine. In Proceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008 (pp. 1766-1770). Article 4709241 (Proceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008). https://doi.org/10.1109/ICYCS.2008.481

@inproceedings{f148c2668a354918a905c326363636db,

title = "Face recognition using scale invariant feature transform and support vector machine",

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.",

keywords = "Face recognition, SIFT feature, Support vector machine (SVM)",

author = "Lichun Zhang and Junwei Chen and Yue Lu and Patrick Wang",

year = "2008",

doi = "10.1109/ICYCS.2008.481",

language = "英语",

isbn = "9780769533988",

series = "Proceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008",

pages = "1766--1770",

booktitle = "Proceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008",

note = "9th International Conference for Young Computer Scientists, ICYCS 2008 ; Conference date: 18-11-2008 Through 21-11-2008",

}

Zhang, L, Chen, J, Lu, Y & Wang, P 2008, Face recognition using scale invariant feature transform and support vector machine. in Proceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008., 4709241, Proceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008, pp. 1766-1770, 9th International Conference for Young Computer Scientists, ICYCS 2008, Zhang Jia Jie, Hunan, China, 18/11/08. https://doi.org/10.1109/ICYCS.2008.481

Face recognition using scale invariant feature transform and support vector machine. / Zhang, Lichun; Chen, Junwei; Lu, Yue et al.
Proceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008. 2008. p. 1766-1770 4709241 (Proceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Face recognition using scale invariant feature transform and support vector machine

AU - Zhang, Lichun

AU - Chen, Junwei

AU - Lu, Yue

AU - Wang, Patrick

PY - 2008

Y1 - 2008

N2 - 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.

AB - 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.

KW - Face recognition

KW - SIFT feature

KW - Support vector machine (SVM)

UR - https://www.scopus.com/pages/publications/58349089249

U2 - 10.1109/ICYCS.2008.481

DO - 10.1109/ICYCS.2008.481

M3 - 会议稿件

AN - SCOPUS:58349089249

SN - 9780769533988

T3 - Proceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008

SP - 1766

EP - 1770

BT - Proceedings of the 9th International Conference for Young Computer Scientists, ICYCS 2008

T2 - 9th International Conference for Young Computer Scientists, ICYCS 2008

Y2 - 18 November 2008 through 21 November 2008

ER -

Face recognition using scale invariant feature transform and support vector machine

Abstract

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Conference

Keywords

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