Shape Similarity System driven by Digital Elevation Models for Non-rigid Shape Retrieval
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Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
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 flattening 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 efficiency.
Description
@inproceedings{10.2312:3dor.20171051,
booktitle = {Eurographics Workshop on 3D Object Retrieval},
editor = {Ioannis Pratikakis and Florent Dupont and Maks Ovsjanikov},
title = {{Shape Similarity System driven by Digital Elevation Models for Non-rigid Shape Retrieval}},
author = {Craciun, Daniela and Levieux, Guillaume and Montes, Matthieu},
year = {2017},
publisher = {The Eurographics Association},
ISSN = {1997-0471},
ISBN = {978-3-03868-030-7},
DOI = {10.2312/3dor.20171051}
}