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

被引:27
作者
Biasotti, S. [1 ]
Cerri, A. [1 ]
Aono, M. [6 ]
Ben Hamza, A. [4 ]
Garro, V. [2 ,3 ]
Giachetti, A. [3 ]
Giorgi, D. [2 ,5 ]
Godil, A. [5 ]
Li, C.
Sanada, C. [6 ]
Spagnuolo, M. [1 ]
Tatsuma, A. [6 ]
Velasco-Forero, S. [7 ]
机构
[1] CNR, Ist Matemat Applicata & Tecnol Informat E Magenes, Genoa, Italy
[2] CNR, Ist Sci & Tecnol Informaz A Faedo, Pisa, Italy
[3] Univ Verona, Dipartimento Informat, I-37100 Verona, Italy
[4] Concordia Univ, Montreal, PQ, Canada
[5] NIST, Gaithersburg, MD 20899 USA
[6] Toyohashi Univ Technol, Dept Comp Sci & Engn, Toyohashi, Aichi, Japan
[7] Natl Univ Singapore, Dept Math, 10 Kent Ridge Crescent, Singapore 117548, Singapore
关键词
Shape retrieval; Shape classification; Textured 3D models; SHAPE RETRIEVAL; COMBINING COLOR; RADIAL SYMMETRY; DESCRIPTORS; SURFACES; FEATURES; GEOMETRY; IMAGES;
D O I
10.1007/s00371-015-1146-3
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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.
引用
收藏
页码:217 / 241
页数:25
相关论文
共 79 条
  • [1] [Anonymous], 2012, AFFINE INVARIANT PHO
  • [2] [Anonymous], IEEE INT C ADV VID S
  • [3] [Anonymous], 2009, Encyclopedia of Distances, DOI DOI 10.1007/978-3-642-00234-21
  • [4] [Anonymous], COEFFICIENT COLOR C
  • [5] [Anonymous], EUR WORKSH 3D OBJ RE
  • [6] [Anonymous], LECT NOTES COMPUTER
  • [7] [Anonymous], CS2006030 UU
  • [8] [Anonymous], THESIS CONCORDIA U M
  • [9] [Anonymous], P 3 INT C SCAL SPAC
  • [10] [Anonymous], 2014, IEEE C COMPUTER VISI