A Boosting method based on SVM for relevance feedback in content-based 3D model retrieval

Tao Wei; Zheng Qin; Xiaoman Cao; Biao Leng

A Boosting method based on SVM for relevance feedback in content-based 3D model retrieval

Tao Wei^*
, Zheng Qin
, Xiaoman Cao
, Biao Leng

^*Corresponding author for this work

School of Computer Science and Engineering

Tsinghua University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

The technique of relevance feedback has been introduced to content-based 3D model retrieval. Support Vector Machine as a learner is one of the classical approaches in relevance feedback. And the Boosting method, as one of the ensemble methods, can establish a strong leaner by combing the component learners. In this paper, a novel relevance feedback mechanism, which makes use of the main idea of boosting and the component SVM, is presented and applied to the content-based 3D model retrieval. The experiments, based on the 3D model database Princeton Shape Benchmark, show that the relevance feedback algorithm can improve the retrieval performance of traditional SVM in 3D model retrieval.

Original language	English
Title of host publication	2nd International Conference on Software Engineering and Data Mining, SEDM 2010
Pages	517-522
Number of pages	6
State	Published - 2010
Event	2nd International Conference on Software Engineering and Data Mining, SEDM 2010 - Chengdu, China Duration: 23 Jun 2010 → 25 Jun 2010

Publication series

Name	2nd International Conference on Software Engineering and Data Mining, SEDM 2010

Conference

Conference	2nd International Conference on Software Engineering and Data Mining, SEDM 2010
Country/Territory	China
City	Chengdu
Period	23/06/10 → 25/06/10

Keywords

Boosting
Content-based 3D model retrieval
Relevance feedback
Support Vector Machine

Cite this

@inproceedings{33d8537d3e46479da3942d2430de4bf1,

title = "A Boosting method based on SVM for relevance feedback in content-based 3D model retrieval",

abstract = "The technique of relevance feedback has been introduced to content-based 3D model retrieval. Support Vector Machine as a learner is one of the classical approaches in relevance feedback. And the Boosting method, as one of the ensemble methods, can establish a strong leaner by combing the component learners. In this paper, a novel relevance feedback mechanism, which makes use of the main idea of boosting and the component SVM, is presented and applied to the content-based 3D model retrieval. The experiments, based on the 3D model database Princeton Shape Benchmark, show that the relevance feedback algorithm can improve the retrieval performance of traditional SVM in 3D model retrieval.",

keywords = "Boosting, Content-based 3D model retrieval, Relevance feedback, Support Vector Machine",

author = "Tao Wei and Zheng Qin and Xiaoman Cao and Biao Leng",

year = "2010",

language = "英语",

isbn = "9788988678213",

series = "2nd International Conference on Software Engineering and Data Mining, SEDM 2010",

pages = "517--522",

booktitle = "2nd International Conference on Software Engineering and Data Mining, SEDM 2010",

note = "2nd International Conference on Software Engineering and Data Mining, SEDM 2010 ; Conference date: 23-06-2010 Through 25-06-2010",

}

Wei, T, Qin, Z, Cao, X & Leng, B 2010, A Boosting method based on SVM for relevance feedback in content-based 3D model retrieval. in 2nd International Conference on Software Engineering and Data Mining, SEDM 2010., 5542868, 2nd International Conference on Software Engineering and Data Mining, SEDM 2010, pp. 517-522, 2nd International Conference on Software Engineering and Data Mining, SEDM 2010, Chengdu, China, 23/06/10.

A Boosting method based on SVM for relevance feedback in content-based 3D model retrieval. / Wei, Tao; Qin, Zheng; Cao, Xiaoman et al.
2nd International Conference on Software Engineering and Data Mining, SEDM 2010. 2010. p. 517-522 5542868 (2nd International Conference on Software Engineering and Data Mining, SEDM 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Boosting method based on SVM for relevance feedback in content-based 3D model retrieval

AU - Wei, Tao

AU - Qin, Zheng

AU - Cao, Xiaoman

AU - Leng, Biao

PY - 2010

Y1 - 2010

N2 - The technique of relevance feedback has been introduced to content-based 3D model retrieval. Support Vector Machine as a learner is one of the classical approaches in relevance feedback. And the Boosting method, as one of the ensemble methods, can establish a strong leaner by combing the component learners. In this paper, a novel relevance feedback mechanism, which makes use of the main idea of boosting and the component SVM, is presented and applied to the content-based 3D model retrieval. The experiments, based on the 3D model database Princeton Shape Benchmark, show that the relevance feedback algorithm can improve the retrieval performance of traditional SVM in 3D model retrieval.

AB - The technique of relevance feedback has been introduced to content-based 3D model retrieval. Support Vector Machine as a learner is one of the classical approaches in relevance feedback. And the Boosting method, as one of the ensemble methods, can establish a strong leaner by combing the component learners. In this paper, a novel relevance feedback mechanism, which makes use of the main idea of boosting and the component SVM, is presented and applied to the content-based 3D model retrieval. The experiments, based on the 3D model database Princeton Shape Benchmark, show that the relevance feedback algorithm can improve the retrieval performance of traditional SVM in 3D model retrieval.

KW - Boosting

KW - Content-based 3D model retrieval

KW - Relevance feedback

KW - Support Vector Machine

UR - https://www.scopus.com/pages/publications/77956501257

M3 - 会议稿件

AN - SCOPUS:77956501257

SN - 9788988678213

T3 - 2nd International Conference on Software Engineering and Data Mining, SEDM 2010

SP - 517

EP - 522

BT - 2nd International Conference on Software Engineering and Data Mining, SEDM 2010

T2 - 2nd International Conference on Software Engineering and Data Mining, SEDM 2010

Y2 - 23 June 2010 through 25 June 2010

ER -

A Boosting method based on SVM for relevance feedback in content-based 3D model retrieval

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Publication series

Conference

Keywords

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