3D Shape Matching by Geodesic Eccentricity

Adrian Ion (1) , Nicole M. Artner (2) , Gabriel Peyré (3) , Salvador B. Lopez Marmol (2) , Walter G. Kropatsch (1) , Laurent D. Cohen (3)

1 PRIP - Pattern Recognition and Image Processing Group
2 PRIT - Pattern Recognition and Image Processing Group
3 CEREMADE - CEntre de REcherches en MAthématiques de la DEcision

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.

Mots clés: Shape matching; eccentricity; geodesic; Fast Marching

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Adrian Ion, Nicole M. Artner, Gabriel Peyré, Salvador B. Lopez Marmol, Walter G. Kropatsch, et al.. 3D Shape Matching by Geodesic Eccentricity. Search in 3D 2008, Jun 2008, Anchorage, Alaska, United States. pp.1-8, ⟨10.1109/CVPRW.2008.4563032⟩. ⟨hal-00419826⟩