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Automatic Categorization of Shots in News Videos Based on the Temporal Relations

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Computational Collective Intelligence

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9330))

Abstract

The development of new methods and technologies of video indexing and retrieval is stimulated by the growing amount of digital video data stored in Internet video collections, TV shows archives, video-on-demand systems, personal video archives offered by Web services, etc. The videos very frequently offered in the Web by broadcast channels are news videos and sports news videos. Content-based indexing of videos is based on the automatic detection of a video structure. A video shot is the main structural video unit. Shots can be of different categories such as intro or final animation, chart or table shots, anchor, reporter, statement, or interview shots, and finally the most informative report shots. The temporal aggregation results in grouping of shots into scenes of a given category. The paper examines the usefulness of the temporal aggregation method to select report shots and non-report shots in a news video.

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Author information

Authors and Affiliations

  1. Department of Information Systems, Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Kazimierz Choroś

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  1. Kazimierz Choroś
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Correspondence to Kazimierz Choroś .

Editor information

Editors and Affiliations

  1. Universidad Complutense de Madrid, Madrid, Spain

    Manuel Núñez

  2. Wroclaw University of Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  3. Computer Science Department, Universidad Autónoma De Madrid, Madrid, Spain

    David Camacho

  4. Wroclaw University of Technology, Wroclaw, Poland

    Bogdan Trawiński

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Choroś, K. (2015). Automatic Categorization of Shots in News Videos Based on the Temporal Relations. In: Núñez, M., Nguyen, N., Camacho, D., Trawiński, B. (eds) Computational Collective Intelligence. Lecture Notes in Computer Science(), vol 9330. Springer, Cham. https://doi.org/10.1007/978-3-319-24306-1_2

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  • DOI: https://doi.org/10.1007/978-3-319-24306-1_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24305-4

  • Online ISBN: 978-3-319-24306-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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