Maximized posteriori attributes selection from facial salient landmarks for face recognition

Authors:
Phalguni Gupta;Dakshina Ranjan Kisku;Jamuna Kanta Sing;Massimo Tistarelli
Affiliations:
Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, India;Department of Computer Science and Engineering, Dr. B. C. Roy Engineering College, Jadavpur University, Durgapur, India;Department of Computer Science and Engineering, Jadavpur University, Kolkata, India;Computer Vision Laboratory, DAP, University of Sassari, Alghero, SS, Italy
Venue:
AST/UCMA/ISA/ACN'10 Proceedings of the 2010 international conference on Advances in computer science and information technology
Year:
2010

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Abstract

This paper presents a robust and dynamic face recognition technique based on the extraction and matching of devised probabilistic graphs drawn on SIFT features related to independent face areas. The face matching strategy is based on matching individual salient facial graph characterized by SIFT features as connected to facial landmarks such as the eyes and the mouth. In order to reduce the face matching errors, the Dempster-Shafer decision theory is applied to fuse the individual matching scores obtained from each pair of salient facial features. The proposed algorithm is evaluated with the ORL and the IITK face databases. The experimental results demonstrate the effectiveness and potential of the proposed face recognition technique also in case of partially occluded faces.