Deformation modeling for robust 3D face matching
Face recognition based on 3D surface matching is promising for overcoming some of the limitations of current 2D image-based face recognition systems. The 3D shape is generally invariant to the pose and lighting changes, but not invariant to the non-rigid facial movement, such as expressions. Collect...
Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1998. - 30(2008), 8 vom: 05. Aug., Seite 1346-57 |
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Format: | Online-Aufsatz |
Sprache: | English |
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2008
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Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
Schlagworte: | Journal Article |
Zusammenfassung: | Face recognition based on 3D surface matching is promising for overcoming some of the limitations of current 2D image-based face recognition systems. The 3D shape is generally invariant to the pose and lighting changes, but not invariant to the non-rigid facial movement, such as expressions. Collecting and storing multiple templates to account for various expressions for each subject in a large database is not practical. We propose a facial surface modeling and matching scheme to match 2.5D facial scans in the presence of both non-rigid deformations and pose changes (multiview) to a 3D face template. A hierarchical geodesic-based resampling approach is applied to extract landmarks for modeling facial surface deformations. We are able to synthesize the deformation learned from a small group of subjects (control group) onto a 3D neutral model (not in the control group), resulting in a deformed template. A user-specific (3D) deformable model is built by combining the templates with synthesized deformations. The matching distance is computed by fitting this generative deformable model to a test scan. A fully automatic and prototypic 3D face matching system has been developed. Experimental results demonstrate that the proposed deformation modeling scheme increases the 3D face matching accuracy |
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Beschreibung: | Date Completed 28.08.2008 Date Revised 20.06.2008 published: Print Citation Status MEDLINE |
ISSN: | 0162-8828 |
DOI: | 10.1109/TPAMI.2007.70784 |