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Advances in Sports Video Summarization – A Review Based on Cricket Videos

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Advances and Trends in Artificial Intelligence. From Theory to Practice (IEA/AIE 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12799))

Abstract

Watching sports videos over streaming sites and television network is one of the most entertaining ways to engage with sports activities. Sports videos like cricket has been viewed by larger audiences than viewing in person. The pandemic since 2020 has changed the world of sports viewing to a larger extent. Some of the sports events are even streamed live through YouTube. The most interesting part of any sports videos is watching the highlights or events of great interest. This is because of the lack of time to watch the entire length of the game. Automatic video summarization is the solution to this. Some of the day long sports like cricket needs the summarization to be very precise and bring the content within few minutes to the audience. There are several attempts in the literature to automatically summarize the sports videos, particularly the game of cricket. In this paper, an attempt has been made to review some of the latest developments in creating the video summary of cricket sports. A brief review of existing methods of video summarization that addresses many sports including soccer, cricket, tennis, and basketball are reviewed at the beginning. Later, the methods that are developed based on latest machine learning and high-performance algorithms are discussed in detail. Towards the end of this paper, a comparison of these methods is presented. The goal is to lead the prospective researchers in the direction where the methods have open avenues and scope to strengthen.

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References

  1. Tang, H., Kwatra, V., Sargin, M., Gargi, U.: Detecting highlights in sports videos: cricket as a test case. In: IEEE International Conference on Multimedia and Expo, Barcelona (2011)

    Google Scholar 

  2. Kolekar, M.H., Sengupta, S.: Event-importance based customized and automatic cricket highlight generation. In: IEEE International Conference on Multimedia and Expo, Toronto, Ont. (2006)

    Google Scholar 

  3. Kolekar, M.H., Sengupta, S.: Caption content analysis based automated cricket highlight generation. In: National Communications Conference (NCC), Mumbai (2008)

    Google Scholar 

  4. Kolekar, M.H., Sengupta, S.: Bayesian network-based customized highlight generation for broadcast soccer videos. IEEE Trans. Broadcast. 2, 195–209 (2015)

    Google Scholar 

  5. Namuduri, K.: Automatic extraction of highlights from a cricket video using MPEG-7 descriptors. In: First International Communication Systems and Networks and Workshops, Bangalore (2009)

    Google Scholar 

  6. Kumar, Y., Gupta, S., Kiran, B., Ramakrishnan, K., Bhattacharyya, C.: Automatic summarization of broadcast cricket videos. In: IEEE 15th International Symposium on Consumer Electronics (ISCE), Singapore (2011)

    Google Scholar 

  7. Ekin, A., Tekalp, A., Mehrotra, R.: Automatic soccer video analysis and summarization. IEEE Trans. Image Process. 12(7), 796–807 (2003)

    Google Scholar 

  8. Shih, H.: A survey of content-aware video analysis for sports. IEEE Trans. Circuits Syst. Video Technol. 28(5), 1212–1231 (2018)

    Google Scholar 

  9. Tavassolipour, M., Karimian, M., Kasaei, S.: Event detection and summarization in soccer videos using Bayesian network and copula. IEEE Trans. Circuits Syst. Video Technol. 24, 291–304 (2014)

    Article  Google Scholar 

  10. Bagheri-Khaligh, A., Raziperchikolaei, R., Moghaddam, M.: A new method for shot classification in soccer sports video based on SVM classifier. In: Proceedings of the 2012 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI), Santa Fe, NM (2012)

    Google Scholar 

  11. Kapela, R., McGuinness, K., O’Connor, N.E.: Real-time field sports scene classification using colour and frequency space decompositions. J. Real-Time Image Process. , 1–13 (2014). https://doi.org/10.1007/s11554-014-0437-7

  12. Fani, M., Yazdi, M., Clausi, D., Wong, A.: Soccer video structure analysis by parallel feature fusion network and hidden-to-observable transferring markov model. IEEE Access 5, 27322–27336 (2017)

    Article  Google Scholar 

  13. Tien, M.-C., Chen, H.-T., Chen, Y.-W., Hsiao, M.-H., Lee, S.-Y.: Shot classification of basketball videos and its application in shooting position extraction. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2007), Honolulu, HI, USA (2007)

    Google Scholar 

  14. Raventos, A., Quijada, R., Torres, L., Tarrés, F.: Automatic summarization of soccer highlights using audio-visual descriptors. Springer Plus (2015)

    Google Scholar 

  15. Gupta, A., Muthaiah, S.: Cricket stroke extraction: Towards creation of a large-scale cricket actions dataset arXiv:1901.03107 [cs.CV] (2019)

  16. Kumar, R., Santhadevi, D., Janet, B.: Outcome classification in cricket using deep learning. In: IEEE International Conference on Cloud Computing in Emerging Markets CCEM, Bengaluru (2019)

    Google Scholar 

  17. Foysal, M.F., Islam, M., Karim, A., Neehal, N.: Shot-net: a convolutional neural network for classifying different cricket shots. In: Santosh, K., Hegadi, R. (eds.) Recent Trends in Image Processing and Pattern Recognition, Springer Singapore (2018). https://doi.org/10.1007/978-981-13-9181-1_10

  18. Gupta, A.: Cricket stroke extraction: towards creation of a large-scale cricket. CoRR, vol. abs/1901.03107 (2019)

    Google Scholar 

  19. Gupta, A., Muthiah, S.: Viewpoint constrained and unconstrained Cricket stroke localization from untrimmed videos. Image Vis. Comput. 100 (2020)

    Google Scholar 

  20. Islam, M., Hassan, T., Khan, S.: A CNN-based approach to classify cricket bowlers based on their bowling actions, Dhaka, Bangladesh (2019)

    Google Scholar 

  21. Harun-Ur-Rashid, M., Khatun, S., Trisha, Z., Neehal, N., Hasan, M.: Crick-net: A Convolutional Neural Network based Classification Approach for Detecting Waist High No Balls in Cricket (2018)

    Google Scholar 

  22. Jothi Shri, S., Jothilakshmi, S.: Crowd video event classification using convolutional neural network. Comput. Commun. 147, 35–39 (2019)

    Google Scholar 

  23. Rafiq, M., Rafiq, G., Agyeman, R., Choi, G., Jin, S.-I.: Scene classification for sports video summarization using transfer learning. Sensors (2020)

    Google Scholar 

  24. Khan, A., Shao, J., Ali, W., Tumrani, S.: Content-aware summarization of broadcast sports videos: an audio–visual feature extraction approach. Neural Process Letter, 1945–1968 (2020)

    Google Scholar 

  25. Javed, A., Bajwa, K., Malik, H., Irtaza, A., Mahmood, M.: A hybrid approach for summarization of cricket videos. In: IEEE International Conference on Consumer Electronics-Asia(ICCE-Asia), Seoul (2016)

    Google Scholar 

  26. Shukla, P., Sadana, H., Verma, D., Elmadjian, C., Ramana, B., Turk, M.: Automatic cricket highlight generation using event-driven and excitement-based features. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Salt Lake City, UT (2018)

    Google Scholar 

  27. Minhas, R., Javed, A., Irtaza, A., Mahmood, M., Joo, Y.: Shot classification of field sports videos using AlexNet Convolutional Neural Network. Appl. Sci. 9(3) (2019)

    Google Scholar 

  28. Gonzalez, A., Bergasa, L., Yebes, J., Bronte, S.: Text location in complex images. In: IEEE ICPR (2012)

    Google Scholar 

  29. Sharma, R., Sankar, K., Jawahar, C.: Fine-grain annotation of cricket videos. In: Proceedings of the 3rd IAPR Asian Conference on Pattern Recognition (ACPR), Kuala Lumpur, Malaysia (2015)

    Google Scholar 

  30. Krizhevsky, A., Sutskever, I., Hinton, G.: Imagenet classification with deep convolutional neural networks. In: Advances in Neural Information Processing Systems;Neural Information Processing System Foundations Inc. 1097–1105 (2012)

    Google Scholar 

  31. Murala, S., Maheshwari, R., Balasubramanian, R.: Local tetra patterns: a new feature descriptor for. IEEE Trans. Image Process 21, 2874–2886 (2012)

    Article  MathSciNet  Google Scholar 

  32. Vadhanam, B.R.J., Mohan, S., Ramalingam, V., Sugumaran, V.: Performance comparison of various decision tree algorithms for classification of advertisement and non-advertisement videos. Indian J. Sci. Technol. 9(1), 48–65

    Google Scholar 

  33. Vani, V., Kumar, R.P., Mohan, S.: Profiling user interactions of 3D complex meshes for predictive streaming and rendering. In: Kumar, S. (ed.) Proceedings of the Fourth International Conference on Signal and Image Processing 2012 (ICSIP 2012). Lecture Notes in Electrical Engineering, vol 221, pp. 457–467, Springer, India (2012). https://doi.org/10.1007/978-81-322-0997-3_41

  34. Rahman, A.A., Saleem, W., Iyer, V.V.: Driving behavior profiling and prediction in KSA using smart phone sensors and MLAs. In: IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT), pp. 34–39 (2019)

    Google Scholar 

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Authors and Affiliations

  1. STEMP, University of the South Pacific, Suva, Fiji

    Vani Vasudevan & Mohan Sellappa Gounder

Authors
  1. Vani Vasudevan
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  2. Mohan Sellappa Gounder
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Correspondence to Mohan Sellappa Gounder .

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Editors and Affiliations

  1. i-SOMET Incorporate Association, Morioka, Japan

    Hamido Fujita

  2. Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

    Ali Selamat

  3. Western Norway University of Applied Sciences, Bergen, Norway

    Jerry Chun-Wei Lin

  4. Texas State University San Marcos, San Marcos, TX, USA

    Moonis Ali

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Vasudevan, V., Sellappa Gounder, M. (2021). Advances in Sports Video Summarization – A Review Based on Cricket Videos. In: Fujita, H., Selamat, A., Lin, J.CW., Ali, M. (eds) Advances and Trends in Artificial Intelligence. From Theory to Practice. IEA/AIE 2021. Lecture Notes in Computer Science(), vol 12799. Springer, Cham. https://doi.org/10.1007/978-3-030-79463-7_29

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  • DOI: https://doi.org/10.1007/978-3-030-79463-7_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-79462-0

  • Online ISBN: 978-3-030-79463-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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