Zhu Liu
ABSTRACT
Video summarization is essential for the user to understand the main theme of video sequences in a short period, especially when the volume of the video is huge and the content is highly redundant. In this paper, we present a video summarization system, built for the rushes summarization task in TRECVID 2008. The goal is to create a video excerpt including objects and events in the video with minimum redundancy and duration (up to 2% of the original video). We first segment a video into shots and then apply a multi-stage clustering algorithm to eliminate similar shots. Frame importance values that depend on both the temporal content variation and the spatial image salience are used to select the most interesting video clips as part of the summarization. We test our system with two output configurations - a dynamic playback rate and at the native playback rate - as a tradeoff between ground truth inclusion rate and ease of browsing. TRECVID evaluation results show that our system achieves a good inclusion rate and verify that the created video summarization is easy to understand.
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Digital Library
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Index Terms
- Brief and high-interest video summary generation: evaluating the AT&T labs rushes summarizations
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