Sequence alignment for redundancy removal in video rushes summarization

ABSTRACT

In this paper, we describe our approach to the TRECVID 2008 BBC Rushes Summarization task. First, we remove junk frames and dynamically accelerate videos according to their motion activity to maximize the content per time unit. Then, we search identical sequences using a sequence alignment algorithm derived from bio-informatics and we identify and structure scenes in videos, then we select one take per scene. We select the most relevant sequences in order to maximize the content and finally, we compose our summary in an original presentation. The produced summaries have been evaluated in the TRECVID campaign.

REFERENCES

• 1: E. Dumont and B. Mérialdo. Rushes video parsing using video sequence alignment. In Submitted to MMM 2009, the 15th International MultiMedia Modeling Conference, 7--9 January 2009, Sophia-Antipolis, France
• 2: Emilie Dumont , Bernard Merialdo, Split-screen dynamically accelerated video summaries, Proceedings of the international workshop on TRECVID video summarization, p.55-59, September 28-28, 2007, Augsburg, Bavaria, Germany [doi>10.1145/1290031.1290041]
• 3: Duy-Dinh Le , Shin'ichi Satoh, National institute of informatics, japan at TRECVID 2007: BBC rushes summarization, Proceedings of the international workshop on TRECVID video summarization, p.70-73, September 28-28, 2007, Augsburg, Bavaria, Germany [doi>10.1145/1290031.1290044]
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• 5: Paul Over , Alan F. Smeaton , George Awad, The trecvid 2008 BBC rushes summarization evaluation, Proceedings of the 2nd ACM TRECVid Video Summarization Workshop, p.1-20, October 31-31, 2008, Vancouver, British Columbia, Canada [doi>10.1145/1463563.1463564]
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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.1 Multimedia Information Systems
          Subjects: Evaluation/methodology

General Terms:
Algorithms, Performance

Keywords:
sequence alignment, video summarization