Godil, A.
(2015),
Retrieval and classification methods for textured 3D models: A comparative study, International Journal of Computer Vision, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=917596
(Accessed January 23, 2025)
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Retrieval and classification methods for textured 3D models: A comparative study
Published
Author(s)
Abstract
This paper presents a comparative study of six methods for the retrieval and classification of tex- tured 3D models, which have been selected as represen- tative of the state of the start and evaluated through 17 runs. To better analyse and control how these meth- ods deal with specific classes of geometric and texture deformations, we built a collection of 572 synthetic tex- tured mesh models, in which each class includes multi- ple texture and geometric modifications of a small set of null models. The results show a challenging, yet lively, scenario and also reveal interesting insights in how to deal with texture information according to different ap- proaches, possibly working in the CIELab as well as in modifications of the RGB colour space.Citation
International Journal of Computer Vision
Pub Type
Journals
Download Paper
Keywords
Shape retrieval , Shape classification , textured 3D models
Citation
Issues
If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.
Created August 25, 2015, Updated February 19, 2017