DocumentCode :
2961834
Title :
Face recognition by fusion of local and global matching scores using DS theory: An evaluation with uni-classifier and multi-classifier paradigm
Author :
Kisku, Dakshina Ranjan ; Tistarelli, Massimo ; Sing, Jamuna Kanta ; Gupta, Puneet
Author_Institution :
Dr. B.C. Eng. Coll., India
fYear :
2009
fDate :
20-25 June 2009
Firstpage :
60
Lastpage :
65
Abstract :
Faces are highly deformable objects which may easily change their appearance over time. Not all face areas are subject to the same variability. Therefore decoupling the information from independent areas of the face is of paramount importance to improve the robustness of any face recognition technique. This paper presents a robust face recognition technique based on the extraction and matching of SIFT features related to independent face areas. Both a global and local (as recognition from parts) matching strategy is proposed. The local strategy is based on matching individual salient facial SIFT features as connected to facial landmarks such as the eyes and the mouth. As for the global matching strategy, all SIFT features are combined together to form a single feature. In order to reduce the identification errors, the Dempster-Shafer decision theory is applied to fuse the two matching techniques. The proposed algorithms are evaluated with the ORL and the IITK face databases. The experimental results demonstrate the effectiveness and potential of the proposed face recognition techniques also in the case of partially occluded faces or with missing information.
Keywords :
decision theory; face recognition; feature extraction; image classification; image fusion; image matching; inference mechanisms; DS theory; Dempster-Shafer decision theory; SIFT feature extraction; face recognition; global matching score; image fusion; local matching score; multiclassifier paradigm; uniclassifier paradigm; Data mining; Decision theory; Eyes; Face detection; Face recognition; Feature extraction; Independent component analysis; Mouth; Robustness; Spatial databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition Workshops, 2009. CVPR Workshops 2009. IEEE Computer Society Conference on
Conference_Location :
Miami, FL
ISSN :
2160-7508
Print_ISBN :
978-1-4244-3994-2
Type :
conf
DOI :
10.1109/CVPRW.2009.5204298
Filename :
5204298
Link To Document :
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