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.
Sequence alignment for redundancy removal in videorushes summarization
TRECVID 2008, ACM International Conference on Multimedia Information Retrieval 2008, October 27-November 01, 2008, Vancouver, BC, Canada
© ACM, 2008. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in TRECVID 2008, ACM International Conference on Multimedia Information Retrieval 2008, October 27-November 01, 2008, Vancouver, BC, Canada http://doi.acm.org/10.1145/1463563.1463572
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