Indexation d’objets 3D par spectre de formes géodésiques 3D (SFG3D)

Abstract

In this paper, we address the problem of 3D object retrieval based on 3D shape descriptors. The proposed approach builds a new descriptor intrinsically invariant to geometric transformations and robust to topology changes and remeshing. The 3D shape spectrum Descriptor (3D SSD), proposed in the MPEG-7 (Zaharia, 2001), is computed on an intrinsic interest point neighborhood. The neighborhood around each interest point is composed of a set of geodesic level curves and radial ones. The level curves correspond to the points at equal geodesic distances from the interest point. The experiments carried out on the SHREC'09 and SHREC'11 datasets show the performance of the proposed descriptor and compare it to further descriptors proposed in the literature (Lian, 2009;2011). MOTS-CLES : indexation 3D, descripteur de formes 3D, voisinage geodesique, mesure de similarite, distance hausdroff, point d'interet.