DocumentCode :
1844623
Title :
Face Recognition Using Scale Invariant Feature Transform and Support Vector Machine
Author :
Zhang, Lichun ; Chen, Junwei ; Lu, Yue ; Wang, Patrick
Author_Institution :
Dept. of Comput. Sci. & Technol., East China Normal Univ., Shanghai
fYear :
2008
fDate :
18-21 Nov. 2008
Firstpage :
1766
Lastpage :
1770
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; image classification; support vector machines; visual databases; ORL database; SVM; Yale face database; face recognition; object recognition; scale invariant feature transform; support vector machine; Application software; Computer science; Educational institutions; Face detection; Face recognition; Object recognition; Robustness; Spatial databases; Support vector machine classification; Support vector machines; Face recognition; SIFT feature; support vector machine (SVM);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3398-8
Electronic_ISBN :
978-0-7695-3398-8
Type :
conf
DOI :
10.1109/ICYCS.2008.481
Filename :
4709241
Link To Document :
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