Automatic adaptive metadata generation for image retrieval

Hideyasu Sasaki; Yasushi Kiyoki

Automatic adaptive metadata generation for image retrieval

Hideyasu Sasaki, Yasushi Kiyoki

Faculty of Environment and Information Studies

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

3 Citations (Scopus)

Abstract

In this paper, we present an automatic adaptive metadata generation system using content analysis of sample images. First, our system screens out improper query images for metadata generation by using CBIR that computes structural similarity between sample images and query images. Second, the system generates metadata by selecting sample indexes attached to the sample images that are structurally similar to query images. Third, the system detects improper metadata and re-generates proper metadata by identifying wrongly selected metadata. Our system has improved metadata generation by 23.5% on recall ratio and 37% on fallout ratio rather than just using the results of content analysis.

Original language	English
Title of host publication	Proceedings - 2005 Symposium on Applications and the Internet Workshops, SAINT2005
Pages	426-429
Number of pages	4
Publication status	Published - 2005 Dec 1
Event	2005 Symposium on Applications and the Internet Workshops, SAINT2005 - Trento, Italy Duration: 2005 Jan 31 → 2005 Feb 4

Publication series

Name	Proceedings - 2005 Symposium on Applications and the Internet Workshops, SAINT2005
Volume	2005

Other

Other	2005 Symposium on Applications and the Internet Workshops, SAINT2005
Country/Territory	Italy
City	Trento
Period	05/1/31 → 05/2/4

ASJC Scopus subject areas

Engineering(all)

Cite this

Automatic adaptive metadata generation for image retrieval. / Sasaki, Hideyasu; Kiyoki, Yasushi.

Proceedings - 2005 Symposium on Applications and the Internet Workshops, SAINT2005. 2005. p. 426-429 1620065 (Proceedings - 2005 Symposium on Applications and the Internet Workshops, SAINT2005; Vol. 2005).

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

Sasaki, H & Kiyoki, Y 2005, Automatic adaptive metadata generation for image retrieval. in Proceedings - 2005 Symposium on Applications and the Internet Workshops, SAINT2005., 1620065, Proceedings - 2005 Symposium on Applications and the Internet Workshops, SAINT2005, vol. 2005, pp. 426-429, 2005 Symposium on Applications and the Internet Workshops, SAINT2005, Trento, Italy, 05/1/31.

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AB - In this paper, we present an automatic adaptive metadata generation system using content analysis of sample images. First, our system screens out improper query images for metadata generation by using CBIR that computes structural similarity between sample images and query images. Second, the system generates metadata by selecting sample indexes attached to the sample images that are structurally similar to query images. Third, the system detects improper metadata and re-generates proper metadata by identifying wrongly selected metadata. Our system has improved metadata generation by 23.5% on recall ratio and 37% on fallout ratio rather than just using the results of content analysis.

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M3 - Conference contribution

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T3 - Proceedings - 2005 Symposium on Applications and the Internet Workshops, SAINT2005

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BT - Proceedings - 2005 Symposium on Applications and the Internet Workshops, SAINT2005

T2 - 2005 Symposium on Applications and the Internet Workshops, SAINT2005

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Automatic adaptive metadata generation for image retrieval

Abstract

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ASJC Scopus subject areas

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