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Video summarization via exploring the global and local importance

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Abstract

Video Summarization is to generate an important or interesting short video from a long video. It is important to reduce the time required to analyze the same archived video by removing unnecessary video data. This work proposes a novel method to generate dynamic video summarization by fusing the global importance and local importance based on multiple features and image quality. First, videos are split into several suitable video clips. Second, video frames are extracted from each video clip, and the center parts of frames are also extracted. Third, for each frame and the center part, the global importance and the local importance are calculated by using a set of features and image quality. Finally, the global importance and the local importance are fused to select an optimal subset for generating video summarization. Extensive experiments are conducted to demonstrate that the proposed method enables to generate high-quality video summarization.

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Acknowledgments

This work was partially supported by the 973 Program (Project No. 2014CB34 7600), the National Natural Science Foundation of China (Grant No. 61522203 and 61772275) and the Natural Science Foundation of Jiangsu Province (Grant BK20140058 and BK20170033).

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Authors and Affiliations

  1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China

    Tongling Hu & Zechao Li

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  1. Tongling Hu
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  2. Zechao Li
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Correspondence to Zechao Li.

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Hu, T., Li, Z. Video summarization via exploring the global and local importance. Multimed Tools Appl 77, 22083–22098 (2018). https://doi.org/10.1007/s11042-017-5479-y

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