Title :
Recognition of Expression-Variant Faces Using SIFT Method
Author :
Ge, Wei ; Xu, Zhiwen ; Shi, Chunlei ; Zhan, Weida
Author_Institution :
Changchun Univ. of Sci. & Technol., Changchun, China
Abstract :
Prior research has shown that the performance of face recognition systems in variant expression condition degrade seriously compared with invariant expression condition. Face recognition with variant expression is a challenging problem. In this paper, SIFT method is proposed to research on face recognition with variant expression. Two experiments using SIFT method are performed on a variant expression face database. In experiment 1, two images of one person with different expression are compared. In experiment 2, two images of different persons with the same expression are compared. Experimental results show that SIFT method could overcome the whole comparability of different faces and extract the local detail features of face. The experiment demostrates the huge potential of SIFT method in application to face recognition with variant expression.
Keywords :
face recognition; feature extraction; SIFT Method; expression-variant face recognition; feature extraction; Databases; Educational institutions; Face recognition; Feature extraction; Image recognition; Lighting; Transforms; SIFT; expression variant; face recognition; local detail feature; matching; whole comparability;
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2012 Fourth International Conference on
Conference_Location :
Mathura
Print_ISBN :
978-1-4673-2981-1
DOI :
10.1109/CICN.2012.171