short-paper

Hybrid image summarization

Authors:

Xian-Sheng Hua,

Shipeng LiAuthors Info & Claims

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

Pages 1217 - 1220

https://doi.org/10.1145/2072298.2071978

Published: 28 November 2011 Publication History

Abstract

In this paper, we address a problem of managing tagged images with hybrid summarization. We formulate this problem as finding a few image exemplars to represent the image set semantically and visually and solve it in a hybrid way by exploiting both visual and textual information associated with images. We propose a novel approach, called Homogeneous and Heterogeneous Message Propagation (H²MP), which extends affinity propagation that only works over homogeneous relations to heterogeneous relations. The summary obtained by our approach is both visually and semantically satisfactory. The experimental results demonstrate the effectiveness and efficiency of the proposed approach.

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Cited By

Qu JChen J(2019)An investigation of benchmark image collections: how different from digital libraries?The Electronic Library10.1108/EL-10-2018-0195Online publication date: 12-Mar-2019
https://doi.org/10.1108/EL-10-2018-0195
Ramesh Kashyap Avon der Weth CCheng ZKankanhalli MAkkermans HFontaine KVermeulen IHouben GWeber M(2018)EPICURE - Aspect-based Multimodal Review SummarizationProceedings of the 10th ACM Conference on Web Science10.1145/3201064.3202917(365-369)Online publication date: 15-May-2018
https://dl.acm.org/doi/10.1145/3201064.3202917
Singla KMukherjee NKoduvely HBose J(2018)Evaluating Usage of Images for App Classificatio2018 15th IEEE India Council International Conference (INDICON)10.1109/INDICON45594.2018.8987165(1-5)Online publication date: Dec-2018
https://doi.org/10.1109/INDICON45594.2018.8987165
Show More Cited By

Index Terms

Hybrid image summarization
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
        Scene understanding
2. Information systems
  1. Information retrieval
    1. Document representation

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Information

Published In

cover image ACM Conferences

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

Copyright © 2011 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: 28 November 2011

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Short-paper

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MM '11

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SIGMM

MM '11: ACM Multimedia Conference

November 28 - December 1, 2011

Arizona, Scottsdale, USA

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

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Citations

Cited By

Qu JChen J(2019)An investigation of benchmark image collections: how different from digital libraries?The Electronic Library10.1108/EL-10-2018-0195Online publication date: 12-Mar-2019
https://doi.org/10.1108/EL-10-2018-0195
Ramesh Kashyap Avon der Weth CCheng ZKankanhalli MAkkermans HFontaine KVermeulen IHouben GWeber M(2018)EPICURE - Aspect-based Multimodal Review SummarizationProceedings of the 10th ACM Conference on Web Science10.1145/3201064.3202917(365-369)Online publication date: 15-May-2018
https://dl.acm.org/doi/10.1145/3201064.3202917
Singla KMukherjee NKoduvely HBose J(2018)Evaluating Usage of Images for App Classificatio2018 15th IEEE India Council International Conference (INDICON)10.1109/INDICON45594.2018.8987165(1-5)Online publication date: Dec-2018
https://doi.org/10.1109/INDICON45594.2018.8987165
Zhang WFu KSun XZhang YSun HWang H(2018)Joint optimisation convex‐negative matrix factorisation for multi‐modal image collection summarisation based on images and tagsIET Computer Vision10.1049/iet-cvi.2017.056813:2(125-130)Online publication date: 9-May-2018
https://dl.acm.org/doi/10.1049/iet-cvi.2017.0568
Samani ZMoghaddam M(2018)A multi-criteria context-sensitive approach for social image collection summarizationSādhanā10.1007/s12046-018-0908-943:9Online publication date: 20-Jul-2018
https://doi.org/10.1007/s12046-018-0908-9
Samani ZMoghaddam M(2017)A knowledge-based semantic approach for image collection summarizationMultimedia Tools and Applications10.1007/s11042-016-3840-176:9(11917-11939)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1007/s11042-016-3840-1
Camargo JGonzález F(2016)Multimodal latent topic analysis for image collection summarizationInformation Sciences: an International Journal10.1016/j.ins.2015.08.044328:C(270-287)Online publication date: 20-Jan-2016
https://dl.acm.org/doi/10.1016/j.ins.2015.08.044
Cheng ZShen JMiao H(2016)The effects of multiple query evidences on social image retrievalMultimedia Systems10.1007/s00530-014-0432-722:4(509-523)Online publication date: 1-Jul-2016
https://dl.acm.org/doi/10.1007/s00530-014-0432-7
Yao YSun A(2016)A Study of Visual and Semantic Similarity for Social Image Search RecommendationInformation Retrieval Technology10.1007/978-3-319-28940-3_27(347-357)Online publication date: 22-Jan-2016
https://doi.org/10.1007/978-3-319-28940-3_27
Seah BBhowmick SSun A(2015)PRISMProceedings of the VLDB Endowment10.14778/2824032.28240888:12(1868-1871)Online publication date: 1-Aug-2015
https://dl.acm.org/doi/10.14778/2824032.2824088
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