Correspondences between Salient Points on 3D Shapes

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@INPROCEEDINGS{wessel-2006-correspondences,
      author = {Wessel, Raoul and Novotni, Marcin and Klein, Reinhard},
      editor = {Kobbelt, L. and Kuhlen, T. and Aach, T. and Westermann, R.},
       pages = {365--372},
       title = {Correspondences between Salient Points on 3D Shapes},
   booktitle = {Vision, Modeling, and Visualization 2006 (VMV 2006)},
        year = {2006},
       month = nov,
   publisher = {Akademische Verlagsgesellschaft Aka GmbH, Berlin},
    abstract = {Establishing correspondences between salient
                points on 3D shapes results in functions mapping
                similar parts of 3D objects. In this paper, we
                present a new method for establishing binary
                correspondences between salient points on 3D
                shapes. Our algorithm is independent of the shape
                representation and the object topology and does
                not require any prepositioning of the objects. Our
                method first detects stable salient points that are
                representative for certain parts of the shape. For
                each of these salient points it then computes an
                associated local shape descriptor. We introduce
                a matching energy between the salient points of
                two shapes which depends on the similarity of
                the descriptors and the spatial relationship of the
                salient points. An iterative optimization scheme
                determines a correspondence mapping between
                the salient points which minimizes this energy.
                The resulting binary correspondences between the
                salient points can be used for applications like
                3D shape retrieval based on similarity estimation,
                classification of 3D objects, editing, and statistical
                shape analysis. It is especially useful as an initialization
                method for approaches relying on prior
                knowledge about corresponding points like cross
                parameterization or morphing.},
        isbn = {3-89838-081-5},
  conference = {Vision, Modeling, and Visualization 2006 (VMV 2006)}
}