A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video summarization preserving dynamic content
Proceedings of the international workshop on TRECVID video summarization
The trecvid 2008 BBC rushes summarization evaluation
TVS '08 Proceedings of the 2nd ACM TRECVid Video Summarization Workshop
The trecvid 2008 BBC rushes summarization evaluation
TVS '08 Proceedings of the 2nd ACM TRECVid Video Summarization Workshop
STIMO: STIll and MOving video storyboard for the web scenario
Multimedia Tools and Applications
A framework for video abstraction systems analysis and modelling from an operational point of view
Multimedia Tools and Applications
Discrimination of media moments and media intervals: sticker-based watch-and-comment annotation
Multimedia Tools and Applications
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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.