A comparison of methods for non-rigid 3D shape retrieval

Zhouhui Lian, Afzal Godil, Benjamin Bustos, Mohamed Daoudi, Jeroen Hermans, Shun Kawamura, Yukinori Kurita, Guillaume Lavoué, Hien Van Nguyen, Ryutarou Ohbuchi, Yuki Ohkita, Yuya Ohishi, Fatih Porikli, Martin Reuter, Ivan Sipiran, Dirk Smeets, Paul Suetens, Hedi Tabia, Dirk Vandermeulen

Research output: Contribution to journalArticlepeer-review

165 Scopus citations

Abstract

Non-rigid 3D shape retrieval has become an active and important research topic in content-based 3D object retrieval. The aim of this paper is to measure and compare the performance of state-of-the-art methods for non-rigid 3D shape retrieval. The paper develops a new benchmark consisting of 600 non-rigid 3D watertight meshes, which are equally classified into 30 categories, to carry out experiments for 11 different algorithms, whose retrieval accuracies are evaluated using six commonly utilized measures. Models and evaluation tools of the new benchmark are publicly available on our web site [1].

Original languageEnglish
Pages (from-to)449-461
Number of pages13
JournalPattern Recognition
Volume46
Issue number1
DOIs
StatePublished - Jan 2013
Externally publishedYes

Keywords

  • 3D shape retrieval
  • Benchmark
  • Non-rigid

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