VIP methods for Sports Video - an Analysis

  • Dr. Aziz Makandar university of pune
  • Daneshwari Mulimani
Keywords: Object detection, tracking, Kabaddi game, image mosaicking, SVM and optical flow method

Abstract

Video Annotation has become challenging process in the field of Sports Video. An every event with respect to the game requires the precise gloss. This has been done with different Video Image Processing(VIP) Techniques using MATLAB tool. This paper elaborates the all efficient video processing methods applied on the different sports videos and these analyzed results will be tested for Kabaddi Game for image mosaicking in the current case study

References

1. 1. R.Manikandan, R.Ramakrishnan “Human Object Detection and Tracking using
Background Subtraction for Sports Applications‟, International Journal of Research in Computer and Communication Engineering Vol. 2, Issue 10, October 2013. 2. Wei-Lwun Lu et al,„Learning to Track and Identify Players from Broadcast Sports Videos‟, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 3. Trupti A. Chopkar1, Shashikant Lahade,‟ Real Time Detection of Moving Object Based On FPGA‟, www.ijser.in ISSN (Online): 2347-3878, Impact Factor (2014): 3.05. 4. Aastha Tiwari et al,‟ Feature Extraction for Object Recognition and Image Classification‟, International Journal of Engineering Research & Technology (IJERT) Vol. 2 Issue 10, October – 2013 IJERTIJERT ISSN: 2278-0181 5. Bahadır KARASULU,‟Review And Evaluation Of Well-Known Methods For Moving Object Detection” AndTracking In Videos‟, Journal Of Aeronautics And Space Technologies July 2010 Volume 4 Number 4 (11-22). VideoProcessingSteps, www.ee.ucr.edu/~amitrc/publications/VideoAnalysisOvervie w.pdf . Nicola Greggio et al, ”Self-Adaptive Gaussian Mixture Models for Real-Time Video Segmentation and Background Subtraction”, IEEE 978-1-42448136-1/10/$26.00_c 2010 7. Gang Liu et al, “Research on action recognition of player in Broadcast sports Video”, International Journal of Multimedia and Ubuquitous Engineering, ISSN: 1975-0080 IJMUE, Vol 9, No 10, pp 297-306, 2014. 8. Z.Zivkovic et al,” Image Segmentation and Feature Extraction for Recognizing Strokes in Tennis Game Videos”, doc.utwente.nl/36135/1/Zivkovic01image.pdf, 2001 9. David Windridge et al,” Rule Induction for Adaptive Sport Video Characterization Using MLN Clause Templates” , Windridge-IEEE 2015. 10. Aseema Mohanty, Sanjivani Shantaiya, “A Survey on Moving Object Detection using Background Subtraction Methods in Video”, International Journal of Computer Applications (0975 – 8887) National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015). 11. Pierre F et al,” The State of the Art in Multiple Object Tracking Under Occlusion in Video Sequences”, “https://www.semanticscholar.org/.../The-State-of-theArt-in-Multiple-Object-Tracking” 2003.
12. Guangyu Zhu et al,” Action Recognition in Broadcast Tennis Video Using Optical Flow and Support Vector Machine”, link.springer.com/chapter/10.1007%2F11754336_9by G Zhu - 2006 –
13. Claudio L. R. Vieira & Ricardo M. L. Barros, ” Automatic rally detection on broadcast tennis videos”, Pages 55-62 | Received 14 Aug 2012, Accepted 13 Jun 2013, Published online: 16 Sep 2013, http://www.tandfonline.com/doi/abs/10.1080/19346182.2 013.819007?journalCode=rtec20 14. Sian Barris, Chris Button, “A Review of VisionBased Motion Analysis in Sport” Human Performance Centre, School of Physical EducationUniversity of OtagoNew Zealand , 07 October 2012 DOI: 10.2165/00007256-200838120-00006.
http://link.springer.com/article/10.2165/00007256200838120-00006.
15. Chetan G Kagalagomba and Sunanda Dixit, “Player Tracking in Sports Video using Optical Flow Analysis”, Springer Science, Business Media Singapore 2017. 16. J Xing, “Multiple Player Tracking in Sports Video: A Dual-Mode Two-Way Bayesian Inference Approach With Progressive Observation Modeling”, IEEE Transactions on Image Processing , Volume: 20, Issue: 6, June 2011. 17. Seema Rajput, S. D. Oza, “Detection And Tracking Of Multiple Moving Objects Based On DWT”, International Journal of Engineering Research & Technology (IJERT) Vol. 2 Issue 1, ISSN: 2278-0181, January- 2013. 18. Ravi Prakash Singh et al, “TIME MOTION ANALYSIS IN SPORTS-A REVIEW”, Academic Sports Scholar ISSN : 2277-3665 Vol. 3 | Issue. 10 | Oct 2014 Impact Factor : 1.3205 (UIF). 19. Shian-Ru Ke et all, “A Review on Video-Based Human Activity Recognition”, 2(2), 88-131; doi:10.3390/computers2020088, Computers 2013.
Published
2018-01-22
How to Cite
Makandar, D. A., & Mulimani, D. (2018). VIP methods for Sports Video - an Analysis. Asian Journal For Convergence In Technology (AJCT) ISSN -2350-1146, 3(3). Retrieved from http://www.asianssr.org/index.php/ajct/article/view/249
Section
Article

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.