3D face recognition using simulated annealing and the surface interpenetration measure

This paper presents a novel automatic framework to perform 3D face recognition. The proposed method uses a Simulated Annealing-based approach (SA) for range image registration with the Surface Interpenetration Measure (SIM), as similarity measure, in order to match two face images. The authenticatio...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1998. - 32(2010), 2 vom: 15. Feb., Seite 206-19
1. Verfasser: Queirolo, Chauã C (VerfasserIn)
Weitere Verfasser: Silva, Luciano, Bellon, Olga R P, Segundo, Maurício Pamplona
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2010
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
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520 |a This paper presents a novel automatic framework to perform 3D face recognition. The proposed method uses a Simulated Annealing-based approach (SA) for range image registration with the Surface Interpenetration Measure (SIM), as similarity measure, in order to match two face images. The authentication score is obtained by combining the SIM values corresponding to the matching of four different face regions: circular and elliptical areas around the nose, forehead, and the entire face region. Then, a modified SA approach is proposed taking advantage of invariant face regions to better handle facial expressions. Comprehensive experiments were performed on the FRGC v2 database, the largest available database of 3D face images composed of 4,007 images with different facial expressions. The experiments simulated both verification and identification systems and the results compared to those reported by state-of-the-art works. By using all of the images in the database, a verification rate of 96.5 percent was achieved at a False Acceptance Rate (FAR) of 0.1 percent. In the identification scenario, a rank-one accuracy of 98.4 percent was achieved. To the best of our knowledge, this is the highest rank-one score ever achieved for the FRGC v2 database when compared to results published in the literature 
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700 1 |a Silva, Luciano  |e verfasserin  |4 aut 
700 1 |a Bellon, Olga R P  |e verfasserin  |4 aut 
700 1 |a Segundo, Maurício Pamplona  |e verfasserin  |4 aut 
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