short-paper

Deep exploration for experiential image retrieval

Authors:

Mark J. Huiskes,

Michael S. LewAuthors Info & Claims

MM '09: Proceedings of the 17th ACM international conference on Multimedia

Pages 673 - 676

https://doi.org/10.1145/1631272.1631385

Published: 19 October 2009 Publication History

Abstract

Experiential image retrieval systems aim to provide the user with a natural and intuitive search experience. The goal is to empower the user to navigate large collections based on his own needs and preferences, while simultaneously providing him with an accurate sense of what the database has to offer. In this paper we integrate a new browsing mechanism called deep exploration with the proven technique of retrieval by relevance feedback. In our approach, relevance feedback focuses the search on relevant regions, while deep exploration facilitates transparent navigation to promising regions of feature space that would normally remain unreachable. Optimal feature weights are determined automatically based on the evidential support for the relevance of each single feature. To achieve efficient refinement of the search space, images are ranked and presented to the user based on their likelihood of being useful for further exploration.

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Cited By

(2016)On interactive learning-to-rank for IRNeurocomputing10.1016/j.neucom.2016.03.084208:C(3-24)Online publication date: 5-Oct-2016
https://dl.acm.org/doi/10.1016/j.neucom.2016.03.084
Mizuno KWu HTakahashi S(2014)Manipulating Bilevel Feature Space for Category-Aware Image ExplorationProceedings of the 2014 IEEE Pacific Visualization Symposium10.1109/PacificVis.2014.58(217-224)Online publication date: 4-Mar-2014
https://dl.acm.org/doi/10.1109/PacificVis.2014.58
Thomee BLew M(2012)Interactive search in image retrieval: a surveyInternational Journal of Multimedia Information Retrieval10.1007/s13735-012-0014-41:2(71-86)Online publication date: 8-Jun-2012
https://doi.org/10.1007/s13735-012-0014-4
Show More Cited By

Index Terms

Deep exploration for experiential image retrieval
1. Information systems
  1. Information retrieval
    1. Evaluation of retrieval results
      1. Relevance assessment
    2. Information retrieval query processing

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Information & Contributors

Information

Published In

cover image ACM Conferences

MM '09: Proceedings of the 17th ACM international conference on Multimedia

October 2009

1202 pages

ISBN:9781605586083

DOI:10.1145/1631272

General Chairs:
Wen Gao
Peking University, China
,
Yong Rui
Microsoft, China
,
Alan Hanjalic
Delft University of Technology, The Netherlands
,
Program Chairs:
Changsheng Xu
Institute of Automation, Chinese Academy of Sciences, China
,
Eckehard Steinbach
Technical University of Munich, Germany
,
Abdulmotaleb El Saddik
University of Ottawa, Canada
,
Michelle Zhou
IBM T. J. Watson Research Center, USA

Copyright © 2009 ACM.

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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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 October 2009

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MM09: ACM Multimedia Conference

October 19 - 24, 2009

Beijing, China

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

(2016)On interactive learning-to-rank for IRNeurocomputing10.1016/j.neucom.2016.03.084208:C(3-24)Online publication date: 5-Oct-2016
https://dl.acm.org/doi/10.1016/j.neucom.2016.03.084
Mizuno KWu HTakahashi S(2014)Manipulating Bilevel Feature Space for Category-Aware Image ExplorationProceedings of the 2014 IEEE Pacific Visualization Symposium10.1109/PacificVis.2014.58(217-224)Online publication date: 4-Mar-2014
https://dl.acm.org/doi/10.1109/PacificVis.2014.58
Thomee BLew M(2012)Interactive search in image retrieval: a surveyInternational Journal of Multimedia Information Retrieval10.1007/s13735-012-0014-41:2(71-86)Online publication date: 8-Jun-2012
https://doi.org/10.1007/s13735-012-0014-4
Kim HLew MZhang ZZhang ZJain RZhuang Y(2010)Social webconsciousnessProceedings of the 1st ACM international workshop on Connected multimedia10.1145/1877911.1877915(3-8)Online publication date: 29-Oct-2010
https://dl.acm.org/doi/10.1145/1877911.1877915

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