MM 2007, 15th international ACM conference on multimedia, September 24-29, 2007, Augsburg, Germany
In this paper, we describe our approach to the TRECVID 2007 BBC Rushes Summarization task. Our processing is composed of several steps. First the video is segmented into shots. Then, one-second video segments are clustered into similarity classes. The most important non-redundant shots are selected such that they maximize the coverage of those similarity classes. Then shots are dynamically accelerated according to their motion activity to maximize the content per time unit. Finally they are optimally grouped by sets of four to be presented using split-screen display. The summaries produced have been evaluated in the TRECVID campaign. We present a first attempt at automating the evaluation process.
Type:
Conference
City:
Augsburg
Date:
2007-09-24
Department:
Data Science
Eurecom Ref:
2303
Copyright:
© ACM, 2007. 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 MM 2007, 15th international ACM conference on multimedia, September 24-29, 2007, Augsburg, Germany http://dx.doi.org/10.1145/1290031.1290041
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