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Novel Mutual Information Analysis of Attentive Motion Entropy Algorithm for Sports Video Summarization

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Book cover Advanced Technologies, Embedded and Multimedia for Human-centric Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 260))

Abstract

This study presents a novel summarization method, which utilizes attentive motion analysis, mutual information, and segmental spectro-temporal subtraction, for generating sports video abstracts. The proposed attentive motion entropy and mutual information are both based on an attentive model. To capture and detect significant segments among a video, this work uses color contrast, intensity contrast, and orientation contrast of frames to calculate saliency maps. Regional histograms of oriented gradients based on human shapes are also adopted at the preliminary stage. In the next step, a new algorithm based on mutual information is proposed to improve the smoothness problem when the system selects the boundaries of motion segments. Meanwhile, differential salient motions and oriented gradients are merged to mutual information analysis, subsequently generating an attentive curve. Furthermore, to remove non-motion boundaries, a smoothing technique based on segmental spectro-temporal subtraction is also used for selecting favorable event boundaries. The experiment results show that our proposed algorithm can detect highlights effectively and generate smooth playable clips. Compared with existing systems, the precision and recall rates of our system outperform their results by 8.6 and 11.1 %, respectively. Besides, smoothness is enhanced by 0.7 on average, which also verified feasibility of our system.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan, Republic of China

    Bo-Wei Chen & Jhing-Fa Wang

  2. Department of Electrical Engineering, Feng Chia University, Taichung, Taiwan, Republic of China

    Karunanithi Bharanitharan

  3. Department of Computer Science and Information Engineering, National Central University, Jhongli, Taiwan, Republic of China

    Jia-Ching Wang

  4. School of Computer Science, Northwestern Polytechnical University, Xi’an, China

    Zhounghua Fu

Authors
  1. Bo-Wei Chen
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  2. Karunanithi Bharanitharan
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  3. Jia-Ching Wang
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  4. Zhounghua Fu
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  5. Jhing-Fa Wang
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Corresponding author

Correspondence to Bo-Wei Chen .

Editor information

Editors and Affiliations

  1. ES Department, National Cheng Kung University, Tainan City, Taiwan

    Yueh-Min Huang

  2. Engineering, National Ilan University Inst. Computer Science & Information, I-Lan, Taiwan

    Han-Chieh Chao

  3. Dept of Computer Sci. and Inf. Bao-Shan Campus, National Changhua University of Education, Changhua City, Taiwan

    Der-Jiunn Deng

  4. Department of Computer Science and Engineering, Seoul University of Science & and Technology (SeoulTech), Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

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Chen, BW., Bharanitharan, K., Wang, JC., Fu, Z., Wang, JF. (2014). Novel Mutual Information Analysis of Attentive Motion Entropy Algorithm for Sports Video Summarization. In: Huang, YM., Chao, HC., Deng, DJ., Park, J. (eds) Advanced Technologies, Embedded and Multimedia for Human-centric Computing. Lecture Notes in Electrical Engineering, vol 260. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7262-5_117

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  • DOI: https://doi.org/10.1007/978-94-007-7262-5_117

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-7261-8

  • Online ISBN: 978-94-007-7262-5

  • eBook Packages: EngineeringEngineering (R0)

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