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VideoMap: An interactive and scalable visualization for exploring video content

  • Research Article
  • Open access
  • Published: 06 May 2016
  • Volume 2, pages 291–304, (2016)
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Computational Visual Media Aims and scope
VideoMap: An interactive and scalable visualization for exploring video content
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  • Cui-Xia Ma1,3,
  • Yang Guo2 &
  • Hong-An Wang1,3 
  • 1288 Accesses

  • Explore all metrics

Abstract

Large-scale dynamic relational data visualization has attracted considerable research attention recently. We introduce dynamic data visualization into the multimedia domain, and present an interactive and scalable system, VideoMap, for exploring large-scale video content. A long video or movie has much content; the associations between the content are complicated. VideoMap uses new visual representations to extract meaningful information from video content. Map-based visualization naturally and easily summarizes and reveals important features and events in video. Multi-scale descriptions are used to describe the layout and distribution of temporal information, spatial information, and associations between video content. Firstly, semantic associations are used in which map elements correspond to video contents. Secondly, video contents are visualized hierarchically from a large scale to a fine-detailed scale. VideoMap uses a small set of sketch gestures to invoke analysis, and automatically completes charts by synthesizing visual representations from the map and binding them to the underlying data. Furthermore, VideoMap allows users to use gestures to move and resize the view, as when using a map, facilitating interactive exploration. Our experimental evaluation of VideoMap demonstrates how the system can assist in exploring video content as well as significantly reducing browsing time when trying to understand and find events of interest.

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Author information

Authors and Affiliations

  1. State Key Lab of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, 100190, China

    Cui-Xia Ma & Hong-An Wang

  2. School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing, 100080, China

    Yang Guo

  3. Beijing Key Lab of Human–Computer Interaction, Institute of Software, Chinese Academy of Sciences, Beijing, 100080, China

    Cui-Xia Ma & Hong-An Wang

Authors
  1. Cui-Xia Ma
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  2. Yang Guo
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  3. Hong-An Wang
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Corresponding author

Correspondence to Cui-Xia Ma.

Additional information

This article is published with open access at Springerlink.com

Cui-Xia Ma received her Ph.D. degree from the Institute of Software, Chinese Academy of Sciences, Beijing, China, in 2003. She is now a professor with the Institute of Software, Chinese Academy of Sciences. Her research interests include human–computer interaction and multimedia computing.

Yang Guo started studying in the Institute of Software, Chinese Academy of Sciences, Beijing, China, in 2013. He is now pursuing a master degree in the Institute of Software, Chinese Academy of Sciences. His research interests include human–computer interaction and multimedia visualization.

Hong-An Wang received his Ph.D. degree from the Institute of Software, Chinese Academy of Sciences, Beijing, China, in 1999. He is now a professor with the Institute of Software, Chinese Academy of Sciences. His research interests include real-time intelligence and user interface.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0), which permits use, duplication, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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Cite this article

Ma, CX., Guo, Y. & Wang, HA. VideoMap: An interactive and scalable visualization for exploring video content. Comp. Visual Media 2, 291–304 (2016). https://doi.org/10.1007/s41095-016-0049-1

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  • Received: 02 February 2016

  • Accepted: 12 March 2016

  • Published: 06 May 2016

  • Issue Date: September 2016

  • DOI: https://doi.org/10.1007/s41095-016-0049-1

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Keywords

  • map metaphor
  • video content visualization
  • sketch-based interaction
  • association analysis
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Avoid common mistakes on your manuscript.

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