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International Conference on Intelligent Computing

ICIC 2021: Intelligent Computing Theories and Application pp 42–53Cite as

VISFF: An Approach for Video Summarization Based on Feature Fusion

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12837))

Abstract

In recent years, the amount of video data has been increasing explosively, and the requirements for video summarization technology have also increased. Video summarization is a summary of the video. By browsing the video summarization, users can quickly understand the content of the video. The traditional video summarization algorithms extract the global features of the video frames to form video summarization. However, these algorithms have obvious disadvantages. Therefore, we propose a method to generate video summarization by fusing the global and local features of video frames, and clustering video frames by DBSCAN algorithm. By comparing with the video summarization manually selected by multiple users, we achieve better results on OVP and YouTube datasets than previous algorithms.

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Acknowledgment

This work was supported in part by the National Natural Science Foundation of China under Grants 61976079 & 61672203, in part by Anhui Natural Science Funds for Distinguished Young Scholar under Grant 170808J08, and in part by Anhui Key Research and Development Program under Grant 202004a05020039.

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Authors and Affiliations

  1. School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, 230009, China

    Wei-Dong Tian, Xiao-Yu Cheng, Bin He & Zhong-Qiu Zhao

Authors
  1. Wei-Dong Tian
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  2. Xiao-Yu Cheng
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  3. Bin He
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  4. Zhong-Qiu Zhao
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Corresponding author

Correspondence to Wei-Dong Tian .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

  3. Shenzhen University, Shenzhen, China

    Jianqiang Li

  4. Far Eastern Branch of the Russian Academy of Sciences, Vladivostok, Russia

    Valeriya Gribova

  5. Department of Computer Science, Liverpool John Moores University, Liverpool, UK

    Abir Hussain

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Tian, WD., Cheng, XY., He, B., Zhao, ZQ. (2021). VISFF: An Approach for Video Summarization Based on Feature Fusion. In: Huang, DS., Jo, KH., Li, J., Gribova, V., Hussain, A. (eds) Intelligent Computing Theories and Application. ICIC 2021. Lecture Notes in Computer Science(), vol 12837. Springer, Cham. https://doi.org/10.1007/978-3-030-84529-2_4

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  • DOI: https://doi.org/10.1007/978-3-030-84529-2_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-84528-5

  • Online ISBN: 978-3-030-84529-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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