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Situation Recognition from Multimodal Data

Published: 06 June 2016 Publication History

Abstract

Situation recognition is the problem of deriving actionable insights from heterogeneous, real-time, big multimedia data to benefit human lives and resources in different applications. This tutorial will discuss the recent developments towards converting multitudes of data streams including weather patterns, stock prices, social media, traffic information, and disease incidents into actionable insights.

References

[1]
V.K. Singh, "Personalized Situation Recognition", Advisor- Ramesh Jain, Ph.D. Thesis, University of California, Irvine. 2012.
[2]
Dousson, C., Gaborit, P., & Ghallab, M. (1993, August). Situation recognition: representation and algorithms. In IJCAI (Vol. 93, pp. 166--172).
[3]
V. K. Singh, M. Gao and R. Jain, "Social pixels: Genesis and evaluation," in Proceedings of the International Conference on Multimedia, 2010, pp. 481--490.
[4]
V. K. Singh, M. Gao and R. Jain, "Situation recognition: an evolving problem for heterogeneous dynamic big multimedia data." Proc. Int. Conf. on Multimedia, 2012
[5]
Wang, Y., & Kankanhalli, M. S. (2015, May). Tweeting Cameras for Event Detection. In Proceedings of the 24th International Conference on World Wide Web (pp. 1231--1241). International World Wide Web Conferences Steering Committee.
[6]
Balduini, M., Della Valle, E., Azzi, M., Larcher, R., Antonelli, F., & Ciuccarelli, P. (2015). Citysensing: visual story telling of city-scale events by fusing social media streams and call data records captured at places and events. IEEE MultiMedia, 22(3)

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  • (2017)BibliographyFrontiers of Multimedia Research10.1145/3122865.3122878(315-377)Online publication date: 19-Dec-2017
  • (2017)Frontiers of Multimedia ResearchundefinedOnline publication date: 19-Dec-2017

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Published In

cover image ACM Conferences
ICMR '16: Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval
June 2016
452 pages
ISBN:9781450343596
DOI:10.1145/2911996
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 June 2016

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Author Tags

  1. concept detection
  2. event detection
  3. events
  4. multimedia data fusion
  5. situation recognition

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  • Tutorial

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ICMR'16
Sponsor:
ICMR'16: International Conference on Multimedia Retrieval
June 6 - 9, 2016
New York, New York, USA

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ICMR '16 Paper Acceptance Rate 20 of 120 submissions, 17%;
Overall Acceptance Rate 254 of 830 submissions, 31%

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Cited By

View all
  • (2017)BibliographyFrontiers of Multimedia Research10.1145/3122865.3122878(315-377)Online publication date: 19-Dec-2017
  • (2017)Frontiers of Multimedia ResearchundefinedOnline publication date: 19-Dec-2017

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