Image retrieval and relevance feedback using peer indexing

Jun Yang; Qing Li; Yueting Zhuang

doi:10.1109/ICME.2002.1035624

Image retrieval and relevance feedback using peer indexing

Jun Yang
, Qing Li
, Yueting Zhuang

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

13 Citations (Scopus)

Abstract

We present the idea of peer indexing - indexing an image by semantically correlated images - and its application in image retrieval. A learning strategy is suggested for automatic acquisition of peer indices from user feedback, and the similarity metric for the peer index is formulated. A cooperative framework is proposed under which the peer index is integrated with low-level features for image retrieval and relevance feedback. Encouraging results on both short-term and long-term retrieval performance of our approach are shown by experiments.

Original language	English
Title of host publication	Proceedings - 2002 IEEE International Conference on Multimedia and Expo, ICME 2002
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	409-412
Number of pages	4
ISBN (Electronic)	0780373049
DOIs	https://doi.org/10.1109/ICME.2002.1035624
Publication status	Published - 1 Jan 2002
Externally published	Yes
Event	2002 IEEE International Conference on Multimedia and Expo, ICME 2002 - Lausanne, Switzerland Duration: 26 Aug 2002 → 29 Aug 2002

Publication series

Name	Proceedings - 2002 IEEE International Conference on Multimedia and Expo, ICME 2002
Volume	2

Conference

Conference	2002 IEEE International Conference on Multimedia and Expo, ICME 2002
Country/Territory	Switzerland
City	Lausanne
Period	26/08/02 → 29/08/02

ASJC Scopus subject areas

Archaeology
Electrical and Electronic Engineering

More information

10.1109/ICME.2002.1035624

Cite this

Yang, J., Li, Q., & Zhuang, Y. (2002). Image retrieval and relevance feedback using peer indexing. In Proceedings - 2002 IEEE International Conference on Multimedia and Expo, ICME 2002 (pp. 409-412). Article 1035624 (Proceedings - 2002 IEEE International Conference on Multimedia and Expo, ICME 2002; Vol. 2). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICME.2002.1035624

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abstract = "We present the idea of peer indexing - indexing an image by semantically correlated images - and its application in image retrieval. A learning strategy is suggested for automatic acquisition of peer indices from user feedback, and the similarity metric for the peer index is formulated. A cooperative framework is proposed under which the peer index is integrated with low-level features for image retrieval and relevance feedback. Encouraging results on both short-term and long-term retrieval performance of our approach are shown by experiments.",

author = "Jun Yang and Qing Li and Yueting Zhuang",

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Yang, J, Li, Q & Zhuang, Y 2002, Image retrieval and relevance feedback using peer indexing. in Proceedings - 2002 IEEE International Conference on Multimedia and Expo, ICME 2002., 1035624, Proceedings - 2002 IEEE International Conference on Multimedia and Expo, ICME 2002, vol. 2, Institute of Electrical and Electronics Engineers Inc., pp. 409-412, 2002 IEEE International Conference on Multimedia and Expo, ICME 2002, Lausanne, Switzerland, 26/08/02. https://doi.org/10.1109/ICME.2002.1035624

Image retrieval and relevance feedback using peer indexing. / Yang, Jun; Li, Qing; Zhuang, Yueting.
Proceedings - 2002 IEEE International Conference on Multimedia and Expo, ICME 2002. Institute of Electrical and Electronics Engineers Inc., 2002. p. 409-412 1035624 (Proceedings - 2002 IEEE International Conference on Multimedia and Expo, ICME 2002; Vol. 2).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AB - We present the idea of peer indexing - indexing an image by semantically correlated images - and its application in image retrieval. A learning strategy is suggested for automatic acquisition of peer indices from user feedback, and the similarity metric for the peer index is formulated. A cooperative framework is proposed under which the peer index is integrated with low-level features for image retrieval and relevance feedback. Encouraging results on both short-term and long-term retrieval performance of our approach are shown by experiments.

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ER -

Image retrieval and relevance feedback using peer indexing

Abstract

Publication series

Conference

ASJC Scopus subject areas

More information

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