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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
3D shape matching by geodesic eccentricity
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Adrian Ion, PRIP, Vienna University of Technology, Austria
Nicole M. Artner, ARC, Smart Systems Division, Austria
Gabriel Peyre, CEREMADE, Université Paris-Dauphine, France
Salvador B. Lopez Marmol, PRIP, Vienna University of Technology, Austria
Walter G. Kropatsch, PRIP, Vienna University of Technology, Austria
Laurent Cohen, CEREMADE, Université Paris-Dauphine, France
This paper makes use of the continuous eccentricity transform to perform 3D shape matching. The eccentricity transform has already been proved useful in a discrete graph-theoretic setting and has been applied to 2D shape matching. We show how these ideas extend to higher dimensions. The eccentricity transform is used to compute descriptors for 3D shapes. These descriptors are defined as histograms of the eccentricity transform and are naturally invariant to euclidean motion and articulation. They show promising results for shape discrimination.
Citation:
Adrian Ion, Nicole M. Artner, Gabriel Peyre, Salvador B. Lopez Marmol, Walter G. Kropatsch, Laurent Cohen, "3D shape matching by geodesic eccentricity," cvprw, pp.1-8, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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