[CLM17] Shape Similarity System driven by Digital Elevation Models for Non-rigid Shape Retrieval

Conférence Internationale avec comité de lecture : Eurographics 3DOR Workshop, April 2017, pp.xx, France,

Auteurs: D. Craciun , G. Levieux , M. Montes

Mots clés: Shape Similarity

Résumé: Shape similarity computation is the main functionality for shape matching and shape retrieval systems. Existing shape similarity frameworks proceed by parameterizing shapes through the use of global and/or local representations computed in the 3D or 2D space. Up to now, global methods have demonstrated their rapidity, while local approaches offer slower, but more accurate solutions. This paper presents a shape similarity system driven by a global descriptor encoded as a Digital Elevation Model (DEM) associated to the input mesh. The DEM descriptor is obtained through the jointly use of a mesh ï¬‚attening technique and a 2D panoramic projection. Experimental results on the public dataset TOSCA [BBK08] and a comparison with state-of-the-art methods illustrate the effectiveness of the proposed method in terms of accuracy and efï¬ciency.

Collaboration: CNAM Paris

BibTeX

@inproceedings {
	CLM17,
	title	=	"{Shape Similarity System driven by Digital Elevation Models for Non-rigid Shape Retrieval}",
	author	=	" D. Craciun and G. Levieux and M. Montes ",
	booktitle	=	"{Eurographics 3DOR Workshop}",
	year	=	2017,
	month	=	"April",
	pages	=	"xx",
	address	=	" France",
}