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Video-based image retrieval

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Shipeng LiAuthors Info & Claims

MM '11: Proceedings of the 19th ACM international conference on Multimedia

Pages 1001 - 1004

https://doi.org/10.1145/2072298.2071923

Published: 28 November 2011 Publication History

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Abstract

Likely variations in the capture conditions (e.g. light, blur, scale, occlusion) and in the viewpoint between the query image and the images in the collection are the factors due to which image retrieval based on the Query-by-Example (QBE) principle is still not reliable enough. In this paper, we propose a novel QBE-based image retrieval system where users are allowed to submit a short video clip as a query to improve the retrieval reliability. Improvement is achieved by integrating the information about different viewpoints and conditions under which object and scene appearances can be captured across different video frames. Rich information extracted from a video can be exploited to generate a more complete query representation than in the case of a single-image query and to improve the relevance of the retrieved results. Our experimental results show that video-based image retrieval (VBIR) is significantly more reliable than the retrieval using a single image as a query.

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Cited By

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Sang MSun ZJia K(2015)Semantic Similarity Based Video Reranking2015 International Conference on Computational Intelligence and Communication Networks (CICN)10.1109/CICN.2015.274(1420-1423)Online publication date: Dec-2015
https://doi.org/10.1109/CICN.2015.274
Bandara YNiroshika UAbeygunawardhane T(2014)Frame feature tracking for speed estimation2014 14th International Conference on Advances in ICT for Emerging Regions (ICTer)10.1109/ICTER.2014.7083875(29-34)Online publication date: Dec-2014
https://doi.org/10.1109/ICTER.2014.7083875
Yao Xue Xueming Qian Baiqi Zhang (2013)Mobile image retrieval using multi-photos as query2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)10.1109/ICMEW.2013.6618255(1-4)Online publication date: Jul-2013
https://doi.org/10.1109/ICMEW.2013.6618255
Show More Cited By

Index Terms

Video-based image retrieval
1. Information systems
  1. Information retrieval

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Published In

MM '11: Proceedings of the 19th ACM international conference on Multimedia

November 2011

944 pages

ISBN:9781450306164

DOI:10.1145/2072298

General Chairs:
K. Selçuk Candan
Arizona State University, USA
,
Sethuraman Panchanathan
Arizona State University, USA
,
Balakrishnan Prabhakaran
University of Texas at Dallas, USA
,
Program Chairs:
Hari Sundaram
Arizona State University, USA
,
Wu-Chi Feng
Portland State University, USA
,
Nicu Sebe
University of Trento, Italy

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: 28 November 2011

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MM '11: ACM Multimedia Conference

November 28 - December 1, 2011

Arizona, Scottsdale, USA

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Sang MSun ZJia K(2015)Semantic Similarity Based Video Reranking2015 International Conference on Computational Intelligence and Communication Networks (CICN)10.1109/CICN.2015.274(1420-1423)Online publication date: Dec-2015
https://doi.org/10.1109/CICN.2015.274
Bandara YNiroshika UAbeygunawardhane T(2014)Frame feature tracking for speed estimation2014 14th International Conference on Advances in ICT for Emerging Regions (ICTer)10.1109/ICTER.2014.7083875(29-34)Online publication date: Dec-2014
https://doi.org/10.1109/ICTER.2014.7083875
Yao Xue Xueming Qian Baiqi Zhang (2013)Mobile image retrieval using multi-photos as query2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)10.1109/ICMEW.2013.6618255(1-4)Online publication date: Jul-2013
https://doi.org/10.1109/ICMEW.2013.6618255
Cai YTong WYang LHauptmann AIp HRui Y(2012)Constrained keypoint quantizationProceedings of the 2nd ACM International Conference on Multimedia Retrieval10.1145/2324796.2324816(1-8)Online publication date: 5-Jun-2012
https://dl.acm.org/doi/10.1145/2324796.2324816

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Image retrieval based on bag of images

Content-based image retrieval by clustering

Theory of keyblock-based image retrieval

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