.png){kind=icon}
.png){kind=icon}
Return
Retrieval and classification methods for textured 3D models: a comparative study
.png){kind=icon}
OA
AI
DOI：10.1007/s00371-015-1146-3.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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.
Keywords:
Shape retrieval
Shape classification
Textured 3D models
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
2.9
Papers:
4.6K
Citations:
6.5K
Organization
View more organizations