A multiple instance learning approach for content based image retrieval using one-class support vector machine

Chengcui Zhang; Xin Chen; Min Chen; Shu Ching Chen; Mei Ling Shyu

doi:10.1109/ICME.2005.1521628

A multiple instance learning approach for content based image retrieval using one-class support vector machine

Chengcui Zhang, Xin Chen, Min Chen, Shu Ching Chen, Mei Ling Shyu

Electrical and Computer Engineering

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

36 Scopus citations

Abstract

Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on One-Class Support Vector Machine (SVM) to solve MIL problem in the region-based Content Based Image Retrieval (CBIR). Relevance Feedback technique is incorporated to provide progressive guidance to the learning process. Performance is evaluated and the effectiveness of our retrieval algorithm has been shown through comparative studies.

Original language	English (US)
Title of host publication	IEEE International Conference on Multimedia and Expo, ICME 2005
Pages	1142-1145
Number of pages	4
DOIs	https://doi.org/10.1109/ICME.2005.1521628
State	Published - 2005
Event	IEEE International Conference on Multimedia and Expo, ICME 2005 - Amsterdam, Netherlands Duration: Jul 6 2005 → Jul 8 2005

Publication series

Name	IEEE International Conference on Multimedia and Expo, ICME 2005
Volume	2005

Other

Other	IEEE International Conference on Multimedia and Expo, ICME 2005
Country/Territory	Netherlands
City	Amsterdam
Period	7/6/05 → 7/8/05

ASJC Scopus subject areas

Engineering(all)

Access to Document

10.1109/ICME.2005.1521628

Cite this

Zhang, C., Chen, X., Chen, M., Chen, S. C., & Shyu, M. L. (2005). A multiple instance learning approach for content based image retrieval using one-class support vector machine. In IEEE International Conference on Multimedia and Expo, ICME 2005 (pp. 1142-1145). [1521628] (IEEE International Conference on Multimedia and Expo, ICME 2005; Vol. 2005). https://doi.org/10.1109/ICME.2005.1521628

A multiple instance learning approach for content based image retrieval using one-class support vector machine. / Zhang, Chengcui; Chen, Xin; Chen, Min; Chen, Shu Ching; Shyu, Mei Ling.

IEEE International Conference on Multimedia and Expo, ICME 2005. 2005. p. 1142-1145 1521628 (IEEE International Conference on Multimedia and Expo, ICME 2005; Vol. 2005).

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

Zhang, C, Chen, X, Chen, M, Chen, SC & Shyu, ML 2005, A multiple instance learning approach for content based image retrieval using one-class support vector machine. in IEEE International Conference on Multimedia and Expo, ICME 2005., 1521628, IEEE International Conference on Multimedia and Expo, ICME 2005, vol. 2005, pp. 1142-1145, IEEE International Conference on Multimedia and Expo, ICME 2005, Amsterdam, Netherlands, 7/6/05. https://doi.org/10.1109/ICME.2005.1521628

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author = "Chengcui Zhang and Xin Chen and Min Chen and Chen, {Shu Ching} and Shyu, {Mei Ling}",

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AB - Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on One-Class Support Vector Machine (SVM) to solve MIL problem in the region-based Content Based Image Retrieval (CBIR). Relevance Feedback technique is incorporated to provide progressive guidance to the learning process. Performance is evaluated and the effectiveness of our retrieval algorithm has been shown through comparative studies.

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A multiple instance learning approach for content based image retrieval using one-class support vector machine

Abstract

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