A comparison of methods for non-rigid 3D shape retrieval
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-...
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| Veröffentlicht in: | Pattern recognition Jg. 46; H. 1; S. 449 - 461 |
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| 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].
► We develop a new benchmark consisting of 600 non-rigid 3D watertight meshes. ► We evaluate and compare 11 non-rigid 3D shape retrieval methods. ► We find that no single method performs best for all kinds of objects. ► Models and evaluation tools of the new benchmark are publicly available. |
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| AbstractList | 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].
► We develop a new benchmark consisting of 600 non-rigid 3D watertight meshes. ► We evaluate and compare 11 non-rigid 3D shape retrieval methods. ► We find that no single method performs best for all kinds of objects. ► Models and evaluation tools of the new benchmark are publicly available. 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]. 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. |
| Author | Tabia, Hedi Reuter, Martin Sipiran, Ivan Suetens, Paul Godil, Afzal Ohbuchi, Ryutarou Hermans, Jeroen Kawamura, Shun Bustos, Benjamin Smeets, Dirk Daoudi, Mohamed Lian, Zhouhui Ohkita, Yuki Kurita, Yukinori Porikli, Fatih Van Nguyen, Hien Lavoué, Guillaume Vandermeulen, Dirk Ohishi, Yuya |
| Author_xml | – sequence: 1 givenname: Zhouhui surname: Lian fullname: Lian, Zhouhui email: lianzhouhui@yahoo.com.cn organization: Institute of Computer Science and Technology, Peking University, Beijing 100871, China – sequence: 2 givenname: Afzal surname: Godil fullname: Godil, Afzal organization: National Institute of Standards and Technology, Gaithersburg, USA – sequence: 3 givenname: Benjamin surname: Bustos fullname: Bustos, Benjamin organization: Department of Computer Science, University of Chile, Chile – sequence: 4 givenname: Mohamed surname: Daoudi fullname: Daoudi, Mohamed organization: Institut TELECOM, France – sequence: 5 givenname: Jeroen surname: Hermans fullname: Hermans, Jeroen organization: Katholieke Universiteit Leuven, Belgium – sequence: 6 givenname: Shun surname: Kawamura fullname: Kawamura, Shun organization: University of Yamanashi, Japan – sequence: 7 givenname: Yukinori surname: Kurita fullname: Kurita, Yukinori organization: University of Yamanashi, Japan – sequence: 8 givenname: Guillaume surname: Lavoué fullname: Lavoué, Guillaume organization: Université de Lyon, CNRS, France – sequence: 9 givenname: Hien surname: Van Nguyen fullname: Van Nguyen, Hien organization: University of Maryland, College Park, USA – sequence: 10 givenname: Ryutarou surname: Ohbuchi fullname: Ohbuchi, Ryutarou organization: University of Yamanashi, Japan – sequence: 11 givenname: Yuki surname: Ohkita fullname: Ohkita, Yuki organization: University of Yamanashi, Japan – sequence: 12 givenname: Yuya surname: Ohishi fullname: Ohishi, Yuya organization: University of Yamanashi, Japan – sequence: 13 givenname: Fatih surname: Porikli fullname: Porikli, Fatih organization: Mitsubishi Electric Research Laboratories, Cambridge, USA – sequence: 14 givenname: Martin surname: Reuter fullname: Reuter, Martin organization: Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical/MIT, USA – sequence: 15 givenname: Ivan surname: Sipiran fullname: Sipiran, Ivan organization: Department of Computer Science, University of Chile, Chile – sequence: 16 givenname: Dirk surname: Smeets fullname: Smeets, Dirk organization: Katholieke Universiteit Leuven, Belgium – sequence: 17 givenname: Paul surname: Suetens fullname: Suetens, Paul organization: Katholieke Universiteit Leuven, Belgium – sequence: 18 givenname: Hedi surname: Tabia fullname: Tabia, Hedi organization: University Lille 1, France – sequence: 19 givenname: Dirk surname: Vandermeulen fullname: Vandermeulen, Dirk organization: Katholieke Universiteit Leuven, Belgium |
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| Keywords | Non-rigid 3D shape retrieval Benchmark Performance evaluation State of the art Three dimensional shape Pattern recognition Object recognition Algorithm performance Volume Object detection Web site Target detection Content analysis |
| Language | English |
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| Snippet | 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... |
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| SubjectTerms | 3D shape retrieval Algorithms Applied sciences Benchmark Benchmarking Categories Computer Science Computer Vision and Pattern Recognition Detection, estimation, filtering, equalization, prediction Exact sciences and technology Finite element method Information Retrieval Information, signal and communications theory Non-rigid Pattern recognition Retrieval Signal and communications theory Signal processing Signal, noise State of the art Telecommunications and information theory Three dimensional |
| Title | A comparison of methods for non-rigid 3D shape retrieval |
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