Computer Science – Computer Vision and Pattern Recognition
Scientific paper
2010-04-12
ISA 2010
Computer Science
Computer Vision and Pattern Recognition
8 pages, 2 figures
Scientific paper
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.
Gupta Phalguni
Kisku Dakshina Ranjan
Sing Jamuna Kanta
Tistarelli Massimo
No associations
LandOfFree
Maximized Posteriori Attributes Selection from Facial Salient Landmarks for Face Recognition does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Maximized Posteriori Attributes Selection from Facial Salient Landmarks for Face Recognition, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Maximized Posteriori Attributes Selection from Facial Salient Landmarks for Face Recognition will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-262240