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Evaluating content-based filters for image and video retrieval

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SIGIR '04: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval

Pages 590 - 591

https://doi.org/10.1145/1008992.1009135

Published: 25 July 2004 Publication History

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Abstract

This paper investigates the level of metadata accuracy required for image filters to be valuable to users. Access to large digital image and video collections is hampered by ambiguous and incomplete metadata attributed to imagery. Though improvements are constantly made in the automatic derivation of semantic feature concepts such as indoor, outdoor, face, and cityscape, it is unclear how good these improvements should be and under what circumstances they are effective. This paper explores the relationship between metadata accuracy and effectiveness of retrieval using an amateur photo collection, documentary video, and news video. The accuracy of the feature classification is varied from performance typical of automated classifications today to ideal performance taken from manually generated truth data. Results establish an accuracy threshold at which semantic features can be useful, and empirically quantify the collection size when filtering first shows its effectiveness.

References

[1]

Ahlberg, C. and Shneiderman, B. Visual Information Seeking: Tight Coupling of Dynamic Query Filters with Starfield Displays. Proc. CHI '94, ACM Press, 313--317.

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[2]

NIST TREC Video Retrieval Evaluation, 2001-current, http://www-nlpir.nist.gov/projects/trecvid/.

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[3]

Worring, M., Smeulders, A.W.M, and Santini, S. Interaction in content-based retrieval: an evaluation of the state-of-the-art. LNCS 1929, Springer-Verlag (2000), 26--36.

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Christel M(2022)Automated Metadata in Multimedia Information Systems: Creation, Refinement, Use in Surrogates, and EvaluationundefinedOnline publication date: 10-Mar-2022
Del Fabro MSchoeffmann KGuggenberger MTaschwer M(2013)A filtering tool to support interactive search in Internet video archives2013 11th International Workshop on Content-Based Multimedia Indexing (CBMI)10.1109/CBMI.2013.6576544(7-10)Online publication date: Jun-2013
Christel MNaphade MNatsev ATesic J(2006)Assessing the Filtering and Browsing Utility of Automatic Semantic Concepts for Multimedia RetrievalProceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop10.1109/CVPRW.2006.31Online publication date: 17-Jun-2006
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Index Terms

Evaluating content-based filters for image and video retrieval
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

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Published In

SIGIR '04: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval

July 2004

624 pages

ISBN:1581138814

DOI:10.1145/1008992

General Chair:
Mark Sanderson
University of Sheffield (UK)
,
Program Chairs:
Kalervo Järvelin
University of Tampere (Finland)
,
James Allan
University of Massachusetts (USA)
,
Peter Bruza
Distributed Systems Technology Centre (Australia)

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 25 July 2004

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SIGIR04: The 27th ACM/SIGIR International Symposium on Information Retrieval 2004

July 25 - 29, 2004

Sheffield, United Kingdom

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Christel M(2022)Automated Metadata in Multimedia Information Systems: Creation, Refinement, Use in Surrogates, and EvaluationundefinedOnline publication date: 10-Mar-2022
Del Fabro MSchoeffmann KGuggenberger MTaschwer M(2013)A filtering tool to support interactive search in Internet video archives2013 11th International Workshop on Content-Based Multimedia Indexing (CBMI)10.1109/CBMI.2013.6576544(7-10)Online publication date: Jun-2013
Christel MNaphade MNatsev ATesic J(2006)Assessing the Filtering and Browsing Utility of Automatic Semantic Concepts for Multimedia RetrievalProceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop10.1109/CVPRW.2006.31Online publication date: 17-Jun-2006
Christel MHauptmann A(2005)The use and utility of high-level semantic features in video retrievalProceedings of the 4th international conference on Image and Video Retrieval10.1007/11526346_17(134-144)Online publication date: 20-Jul-2005
Hauptmann AChristel MSchulzrinne HDimitrova NSasse AMoon SLienhart R(2004)Successful approaches in the TREC video retrieval evaluationsProceedings of the 12th annual ACM international conference on Multimedia10.1145/1027527.1027681(668-675)Online publication date: 10-Oct-2004

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Multi-class relevance feedback content-based image retrieval

Content-based image retrieval by clustering

Localized Content-Based Image Retrieval

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