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Potential and Limitations of Kinect for Badminton Performance Analysis and Profiling

Affiliations

  • School of Computing, University College of Technology Sarawak, 96000 Sibu, Sarawak, Malaysia

Abstract


Objectives: Badminton performance analysis and profiling are essential steps in badminton coaching in order to identify the strengths and weaknesses of an athlete. Methods: In this paper, we investigated and identified the key potential and limitations of the Microsoft Kinect sensor for badminton performance analysis, particularly on novice badminton player. A survey was conducted during badminton event of SUKMA in order to determine which strokes are important to novice level player, where participants include coaches from different states of Malaysia. The essential strokes were then analyzed by Microsoft Kinect sensor. Findings: The survey results indicated that there are four main strokes to be mastered by novice level player, such as clear, net, lift and smash. Moreover, the key selected badminton strokes as identified by expert coaches such as forehand crosscourt lift, backhand touch net, backhand lift, forehand lift, forehand push net, backhand clear, backhand push net, forehand touch net and forehand clear can be measured and analyzed accurately and consistently with Microsoft Kinect sensor. However, the sensor measurements are limited for badminton strokes such as static smash, jump smash and overhead forehand clear. The major reason for such limitation is mainly due to occlusions and loss of acquisition data due to fast moving motion. Improvement: Therefore, the current performance analysis algorithm using skeleton information will be incorporated with color information in future to resolve the occlusion issue.

Keywords

Badminton, Depth Map, Kinect, Performance Analysis, Performance Profiling.

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References


  • Franks I, Hughes M. Notational analysis of sport: Systems for better coaching and performance in sport. 2nd ed. Routledge Press; 2004.
  • Richards H. Distance learning pack: Performance profiling. University of Edinburgh; 2008.
  • Jones G. The role of performance profiling in cognitive behavioural interventions in sport. The Sport Psychologist. 1993 Jun; 7(2):160–72.
  • Weston N, Greenless I, Thelwell R. Athlete perceptions of the impacts of performance profiling. International Journal of Sport and Exercise Psychology. 2011 Jun; 9(2):173–88.
  • Andrew B, David T, Alexander JJ. Coaches’ perceptions of the potential use of performance analysis in badminton. International of Performance Analysis in Sport. 2012 Aug; 12(2):452–67.
  • Dario S, Dragan M, Goran S. Performance analysis in sport. Proceeding of 4th International Scientific Conference Contemporary Kinesiology. Faculty of Kinesiology, Unversity of Split; Croatia. 2012. p. 1–8.
  • Nunes JF, Moreira PM, Tavares JMR. Human motion analysis and simulation tools: A survey. Handbook of Research on Computational Simulation and Modeling in Engineering, IGI Global; 2016. p. 1–30.
  • Teu KK, Kim W, Tan J, Fuss FK. Using dual Euler angles for the analysis of arm movement during badminton smash. Sport Engineering. 2005 Jan; 8(3):171–8.
  • Huang HC, Lin CT, Hu CS. Analysis of selection indicators of badminton players by the delphi method and analytic hierarchy process. International Journal of Computer Science and Information Technology. 2015 Feb; 7(1):19–31.
  • Salim MS, Lim HN, Salim MN, Baharuddin MY. Motion analysis of arm movement during badminton smash. Proceeding of 2010 IEEE EMBS Conference on Biomedical Engineering and Sciences; Malaysia. 2010. p. 111–4.
  • Nagasawa M, Hatori Y, Kakuta M, Hayashi T, Sekine Y. Smash motion analysis for badminton from image. Proceeding of IIEEJ 3rd Image Electronics and Visual Computing Workshop; Malaysia. 2012.
  • Hussain I, Bari MA. Kinematical analysis of forehand and backhand smash in badminton. Innovative Systems Design and Engineering. 2011 Nov; 2(7):20–5.
  • Ning Y. Research of badminton forehand smash technology based on biomechanical analysis. Journal of Chemical and Pharmaceutical Research. 2013 Nov; 5(11):172–7.
  • Teng SL, Paramesran R. Detection of service activity in a badminton game. Proceeding of TENCON 2011 - IEEE Region 10 Conference; Indonesia. 2011. p. 312–5.
  • Yoshikawa F, Kobayashi T, Watanabe K, Otsu N. Automated service scene detection for badminton game analysis using CHLAC and MRA. World Academy of Science, Engineering and Technology. 2010 Feb; 4:841–4.
  • Hussain I, Ahmed S, Bari MA, Ahmad A, Mohammad A, Khan A. Analysis of arm movement in badminton of forehand long and short service. Innovative Systems Design and Engineering. 2011 Aug; 2(3).
  • Liu G, Zhang D, Li H. Research on action recognition of player in broadcast sports video. International Journal of Multimedia and Ubiquitous Engineering. 2014; 9(10):297–306.
  • Tsai CL, Chang SS. Biomechanical analysis of differences in badminton smash and jump smash between Taiwan elite and collegiate player. Proceeding of XVI International Symposium on Biomechanics in Sports; Germany. 1998. p. 259–62.
  • Chang T, Chan K. Local sensor system for badminton smash analysis. Proceeding of 2009 IEEE Instrumentation and Measurement Technology Conference; Singapore. 2009. p. 883–8.
  • Ting HY, Sim KS, Abas FS. Kinect-based badminton movement recognition and analysis system. International Journal of Computer Science in Sport. 2015 Jan; 14(2):25–41.
  • Cabello Manrique D, Gonzalez-Badillo JJ. Analysis of the characteristics of competitive badminton. British Journal of Sports Medicine. 2003 Feb; 37(1):62–6.
  • Giles J. Inside the race to hack the Kinect. The New Scientist. 2010 Dec; 208(2789):22–3.
  • Dong J. Study on badminton system with auxiliary training based on Kinect motion capture. Computer Modelling and New Technologies. 2013; 17(5D):97–100.
  • He ZD, Hu RM, Xu JC. The development of badminton auxiliary training system based on Kinect motion capture. Advanced Materials Research. 2014 May; 926-930:2735–8.
  • Ting HY, Sim KS, Abas FS. Kinect-based badminton action analysis system. Advanced Materials Research. 2014 Oct; 1042:94–9.
  • Ting HY, Sim KS, Abas FS. Automatic badminton action recognition using RGB-D sensor. Advanced Materials Research. 2014 Oct; 1042:89–93.
  • Obdrzalek S, Kurillo G, Ofli F, Bajcsy R, Seto E, Jimison H, Pavel M. Accuracy and robustness of Kinect pose estimation in the context of coaching of elderly population. Proceeding of 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; USA. 2012. p. 1188–93.
  • Wei T, Lee B, Qiao Y, Kitsikidis A, Dimitropoulos K, Grammalidis N. Experimental study of skeleton tracking abilities from Microsoft kinect non-frontal views. Proceeding of 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video; Portugal. 2015. p. 1–4.
  • Woodward M. Badminton coach education coaches' manual level 1. Badminton World Federation; 2011.
  • Badminton basics for beginners. 2016. Available from: http://www.masterbadminton.com/badminton-basics.html

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