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.Comment: 8 pages, 2 figure