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Retrieval and classification methods for textured 3D models: a comparative study

Academic Article
Publication Date:
2016
abstract:
This paper presents a comparative study of six methods for the retrieval and classification of textured 3D models, which have been selected as representative of the state of the art. To better analyse and control how methods deal with specific classes of geometric and texture deformations, we built a collection of 572 synthetic textured mesh models, in which each class includes multiple texture and geometric modifications of a small set of null models. Results show a challenging, yet lively, scenario and also reveal interesting insights into how to deal with texture information according to different approaches, possibly working in the CIELab as well as in modifications of the RGB colour space.
Iris type:
01.01 Articolo in rivista
Keywords:
Shape classification; Shape retrieval; Textured 3D models; Computer Graphics
List of contributors:
Garro, Valeria; Spagnuolo, Michela; Biasotti, SILVIA MARIA; Giorgi, Daniela; Cerri, Andrea
Authors of the University:
BIASOTTI SILVIA MARIA
GIORGI DANIELA
SPAGNUOLO MICHELA
Handle:
https://iris.cnr.it/handle/20.500.14243/292072
Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/292072/95450/prod_334059-doc_168240.pdf
Published in:
THE VISUAL COMPUTER
Journal
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URL

http://link.springer.com/article/10.1007%2Fs00371-015-1146-3
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