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ABSTRACT
In this paper, we propose an original framework for description and matching of three dimensional faces for recognition purposes. Basic traits of a face are encoded by extracting iso-geodesic stripes from the surface of a face model. A compact representation is then constructed through a modeling technique capable to express the basic shape of iso-geodesic stripes and quantitatively measure their spatial relationships in a three dimensional space. This information is encoded in an attributed relational graph. In this way,the structural similarity between two face models is evaluated by matching their corresponding graphs.Experimental results on a 3D face database and baseline comparison show that the proposed solution attains high face recognition accuracy and is reasonably robust to facial expression and pose changes.
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