Multi-document video summarization

Most previous works on video summarization target on a single video document. With the popularity of video corpus (e.g. news video archives) and Web videos, video article that consists of a set of relevant videos are frequently confronted by users. By the traditional single-document summarization, these videos are treated independently and the results are usually redundant due to the lack of inter-video analysis. To efficiently manage video articles, in this paper, we propose an approach for multi-document video summarization by exploring the redundancy between different videos. The importance of keyframes is first measured by the content inclusion based on intra- and inter-video similarities. We then propose a minimum description length (MDL) for automatically determining the appropriate length of the summary. Finally a video summary is generated for users to browse the content of the whole video article. We show that multi-document video summarization presents more elegant and informative summaries compared with single-document approach.