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

dc.contributor.authorCraciun, Danielaen_US
dc.contributor.authorLevieux, Guillaumeen_US
dc.contributor.authorMontes, Matthieuen_US
dc.contributor.editorIoannis Pratikakis and Florent Dupont and Maks Ovsjanikoven_US
dc.date.accessioned2017-04-22T17:17:41Z
dc.date.available2017-04-22T17:17:41Z
dc.date.issued2017
dc.description.abstractShape 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.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationEurographics Workshop on 3D Object Retrieval
dc.identifier.doi10.2312/3dor.20171051
dc.identifier.isbn978-3-03868-030-7
dc.identifier.issn1997-0471
dc.identifier.pages51-54
dc.identifier.urihttps://doi.org/10.2312/3dor.20171051
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/3dor20171051
dc.publisherThe Eurographics Associationen_US
dc.subjectDesign Methodology [Pattern Recognition]
dc.subjectI.5.1
dc.subjectPattern analysis
dc.titleShape Similarity System driven by Digital Elevation Models for Non-rigid Shape Retrievalen_US
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