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A Unified Geolocation Framework for Web Videos

Authors:

Yongdong Zhang,

Jintao LiAuthors Info & Claims

ACM Transactions on Intelligent Systems and Technology (TIST), Volume 5, Issue 3

Article No.: 49, Pages 1 - 22

https://doi.org/10.1145/2533989

Published: 17 July 2014 Publication History

Abstract

In this article, we propose a unified geolocation framework to automatically determine where on the earth a web video was shot. We analyze different social, visual, and textual relationships from a real-world dataset and find four relationships with apparent geography clues that can be used for web video geolocation. Then, the geolocation process is formulated as an optimization problem that simultaneously takes the social, visual, and textual relationships into consideration. The optimization problem is solved by an iterative procedure, which can be interpreted as a propagation of the geography information among the web video social network. Extensive experiments on a real-world dataset clearly demonstrate the effectiveness of our proposed framework, with the geolocation accuracy higher than state-of-the-art approaches.

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Cited By

Tian CZhu XHu ZMa J(2021)A transfer approach with attention reptile method and long-term generation mechanism for few-shot traffic predictionNeurocomputing10.1016/j.neucom.2021.03.068452(15-27)Online publication date: Sep-2021
https://doi.org/10.1016/j.neucom.2021.03.068
Li ZLang CFeng JLi YWang TFeng S(2019)Co-saliency Detection with Graph MatchingACM Transactions on Intelligent Systems and Technology10.1145/331387410:3(1-22)Online publication date: 12-Apr-2019
https://dl.acm.org/doi/10.1145/3313874
Zhang DFu HHan JBorji ALi X(2018)A Review of Co-Saliency Detection AlgorithmsACM Transactions on Intelligent Systems and Technology10.1145/31586749:4(1-31)Online publication date: 30-Jan-2018
https://dl.acm.org/doi/10.1145/3158674
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Index Terms

A Unified Geolocation Framework for Web Videos
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
      2. Computer vision tasks
        Scene understanding
2. Information systems
  1. Information systems applications

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Information & Contributors

Information

Published In

cover image ACM Transactions on Intelligent Systems and Technology

ACM Transactions on Intelligent Systems and Technology Volume 5, Issue 3

Special Section on Urban Computing

September 2014

361 pages

ISSN:2157-6904

EISSN:2157-6912

DOI:10.1145/2648782

Editor:
Qiang Yang
Hong Kong University of Science and Technology, Hong Kong

Issue’s Table of Contents

Copyright © 2014 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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 July 2014

Accepted: 01 September 2013

Revised: 01 July 2013

Received: 01 March 2013

Published in TIST Volume 5, Issue 3

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National Natural Science Foundation of China
Ministry of Science and Technology of the People's Republic of China
Beijing New Star Project on Science and Technology (2007B071)

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Cited By

Tian CZhu XHu ZMa J(2021)A transfer approach with attention reptile method and long-term generation mechanism for few-shot traffic predictionNeurocomputing10.1016/j.neucom.2021.03.068452(15-27)Online publication date: Sep-2021
https://doi.org/10.1016/j.neucom.2021.03.068
Li ZLang CFeng JLi YWang TFeng S(2019)Co-saliency Detection with Graph MatchingACM Transactions on Intelligent Systems and Technology10.1145/331387410:3(1-22)Online publication date: 12-Apr-2019
https://dl.acm.org/doi/10.1145/3313874
Zhang DFu HHan JBorji ALi X(2018)A Review of Co-Saliency Detection AlgorithmsACM Transactions on Intelligent Systems and Technology10.1145/31586749:4(1-31)Online publication date: 30-Jan-2018
https://dl.acm.org/doi/10.1145/3158674
Delbruel SFrey DTaiani F(2016)Exploring the Use of Tags for Georeplicated Content Placement2016 IEEE International Conference on Cloud Engineering (IC2E)10.1109/IC2E.2016.37(172-181)Online publication date: Apr-2016
https://doi.org/10.1109/IC2E.2016.37
Yin YZhang LZimmermann RHauptmann ANgo CXue XJiang YSnoek CVasconcelos N(2015)Exploiting Spatial Relationship between Scenes for Hierarchical Video GeotaggingProceedings of the 5th ACM on International Conference on Multimedia Retrieval10.1145/2671188.2749354(363-370)Online publication date: 22-Jun-2015
https://dl.acm.org/doi/10.1145/2671188.2749354

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