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  4. SHREC'14 Track: Large scale comprehensive 3D shape retrieval
 
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2014
Conference Paper
Title

SHREC'14 Track: Large scale comprehensive 3D shape retrieval

Abstract
The objective of this track is to evaluate the performance of 3D shape retrieval approaches on a large-sale comprehensive 3D shape database that contains different types of models, such as generic, articulated, CAD and architecture models. The track is based on a new comprehensive 3D shape benchmark, which contains 8,987 triangle meshes that are classified into 171 categories. The benchmark was compiled as a superset of existing benchmarks and presents a new challenge to retrieval methods as it comprises generic models as well as domainspecific model types. In this track, 14 runs have been submitted by 5 groups and their retrieval accuracies were evaluated using 7 commonly used performance metrics.
Author(s)
Li, Bo
Texas State University
Lu, Yijuan
Texas State University
Li, Chunyuan
National Institute of Standards and Technology
Godil, Afzal
National Institute of Standards and Technology
Schreck, Tobias
Univ. Konstanz
Aono, Masaki
Toyohashi Univ. of Technology
Chen, Qiang
Chongqing Univ. of Computer Science
Chowdhury, Nihad Karim
Toyohashi Univ. of Technology
Fang, Bin
Chongqing Univ.
Furuya, Takahiko
Univ. of Yamanashi
Johan, Henry
Fraunhofer Research Centre for Interactive Digital Media IDM@NTU  
Kosaka, Ryuichi
Toyohashi Univ. of Technology
Koyanagi, Hitoshi
Toyohashi Univ. of Technology
Ohbuchi, Ryutarou
Univ. of Yamanashi
Tatsuma, Atsushi
Toyohashi Univ. of Technology
Mainwork
Eurographics Workshop on 3D Object Retrieval, EG 3DOR 2014  
Conference
Workshop on 3D Object Retrieval (EG 3DOR) 2014  
DOI
10.2312/3dor.20141059
Language
English
IDM@NTU  
Keyword(s)
  • large scale retrieval

  • shape matching

  • shape retrieval

  • Business Field: Virtual engineering

  • Research Area: Computer graphics (CG)

  • Research Area: Computer vision (CV)

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