Using a Rank Fusion Technique to Improve Shot Boundary Detection Effectiveness

  • M. Eduardo Ares
  • Álvaro Barreiro
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5717)


Achieving high effectiveness in Shot Boundary Detection (SBD) paves the way for high-level analysis of the video (keyframe extraction, story segmentation, etc.), which makes this step very important. Thus, the SBD problem has been extensively addressed, and many approaches have been proposed. As these approaches have their own different strengths and weaknesses, merging the outcomes of different detectors in order to obtain a better detector comes naturally. In this paper we propose an approach to SBD which takes into account the outcomes of two shot boundary detectors, using a rank fusion technique. This new detector is tested with videos from the TRECVid initiative, finding that it outperforms the two original methods. Moreover, the computation of this merging method is very fast, so it is very attractive for an operational environment.


Shot Boundary Borda Count Rank Aggregation Shoot Boundary Detection Merging Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • M. Eduardo Ares
    • 1
  • Álvaro Barreiro
    • 1
  1. 1.IRLab, Department of Computer ScienceUniversity of A CoruñaA CoruñaSpain

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