Abstract
Video summarization is a significant scheme to organize massive video data, and implement a meaningful rapid navigation of video. In this paper, we propose a hierarchical video summarization approach based on video structure and highlight. We extract video structure unit, and measure the unit (frame, shot and scene) importance rank based on visual and audio attention models. According to the unit importance rank, the skim ratio and key frame ratio are assigned to the different video units. Thus we achieve a hierarchical video summary. Experimental results show the excellent performance of the approach.
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Geng, Y., Xu, D., Feng, S. (2006). Hierarchical Video Summarization Based on Video Structure and Highlight. In: Yeung, DY., Kwok, J.T., Fred, A., Roli, F., de Ridder, D. (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2006. Lecture Notes in Computer Science, vol 4109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11815921_24
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DOI: https://doi.org/10.1007/11815921_24
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