Effectiveness of Video Segmentation Techniques for Different Categories of Videos

  • Authors:
  • Kazimierz Choroś;Michał Gonet

  • Affiliations:
  • Wrocław University of Technology, Institute of Applied Informatics, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland, e-mail: choros@pwr.wroc.pl;Wrocław University of Technology, Institute of Applied Informatics, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland, e-mail: mgonet@vp.pl

  • Venue:
  • Proceedings of the 2008 conference on New Trends in Multimedia and Network Information Systems
  • Year:
  • 2008

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Abstract

Visual retrieval systems as well as Internet search engines demand efficient techniques of indexing to facilitate fast access to the required video or to the required video sequences in the video databases. Digital video databases are more and more frequently implemented not only in the Internet network but also in local networks and even in local personal computers. Different approaches to digital video indexing are applied: textual approach, extraction and representation of technical or structural features, content-based analysis, and finally segmentation. The segmentation process leads to the partition of a given video into a set of meaningful and individually manageable segments, which then can serve as basic units for indexing. Video has temporal properties such as camera motion, object movements on the scene, sequential composition, and interframe relationships. An effective segmentation technique is able to detect not only abrupt changes but also gradual scene changes, such as fade and dissolve transitions. The nature of movies, mainly the style of video editing has an influence on the effectiveness of temporal segmentation methods. The effectiveness of four methods was analyzed for five different categories of movie: TV talk-show, documentary movie, animal video, action & adventure, and pop music video. The cuts have been recognized as well as cross dissolve effects. The tests have shown that the specific nature of videos has an important influence on the effectiveness of temporal segmentation methods.