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NBA Basketball Video Summarization for News Report via Hierarchical-Grained Deep Reinforcement Learning

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Image and Graphics (ICIG 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12890))

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Abstract

At present, the demand for short video generation is increasing, especially for sports news report, which urgently needs automatic video summarization methods to reduce time and labor cost. This paper focuses on NBA basketball videos and seeks for the actual needs of news report on sports video summarization. We propose a hierarchical-grained deep reinforcement learning framework to generate short basketball video. For a long basketball game video, we propose a hierarchical-grained subshot segmentation algorithm, which takes into account both semantics and objective factors, and preserves spatiotemporal consistency. Then we select candidate frames through a news element enhanced deep reinforcement learning framework. On this basis, a news report oriented video summarization algorithm based on probability sampling is implemented with the fusion of multi-game and multi-news elements. Experimental results on the NBA dataset newly collected by us demonstrate the effectiveness of the proposed framework. Moreover, the proposed method is able to highlight the video content including well preserved news elements.

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Notes

  1. 1.

    https://github.com/conniemy/BasketballVideo.

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Acknowledgments

This work was funded by the Key Research and Development Plan of Zhejiang Province (No. 2019C03131) and the Basic Public Welfare Research Project of Zhejiang Province (No. LGF21F020004).

Author information

Authors and Affiliations

  1. Intelligent Media Institute, Communication University of Zhejiang, Hangzhou, China

    Naye Ji, Shiwei Zhao, Qiang Lin, Dingguo Yu & Youbing Zhao

  2. Key Lab of Film and TV Media Technology of Zhejiang Province, Hangzhou, China

    Naye Ji, Qiang Lin, Dingguo Yu & Youbing Zhao

  3. School of Software Technology, Zhejiang University, Hangzhou, China

    Shiwei Zhao

Authors
  1. Naye Ji
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  2. Shiwei Zhao
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  3. Qiang Lin
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  4. Dingguo Yu
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  5. Youbing Zhao
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Corresponding author

Correspondence to Youbing Zhao .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Yuxin Peng

  2. Tsinghua University, Beijing, China

    Shi-Min Hu

  3. Tampere University, Tampere, Finland

    Moncef Gabbouj

  4. Zhejiang University, Hangzhou, China

    Kun Zhou

  5. Technion – Israel Institute of Technology, Haifa, Israel

    Michael Elad

  6. Tsinghua University, Beijing, China

    Kun Xu

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Ji, N., Zhao, S., Lin, Q., Yu, D., Zhao, Y. (2021). NBA Basketball Video Summarization for News Report via Hierarchical-Grained Deep Reinforcement Learning. In: Peng, Y., Hu, SM., Gabbouj, M., Zhou, K., Elad, M., Xu, K. (eds) Image and Graphics. ICIG 2021. Lecture Notes in Computer Science(), vol 12890. Springer, Cham. https://doi.org/10.1007/978-3-030-87361-5_58

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  • DOI: https://doi.org/10.1007/978-3-030-87361-5_58

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87360-8

  • Online ISBN: 978-3-030-87361-5

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