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Development of a markerless optical motion capture system for daily use of training in swimming

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Abstract

The main objective of this research was to develop a markerless optical motion capture system that can be used for daily use in swimming training. The butterfly stroke was targeted since it is considered bilaterally symmetric in motion. The system consisted of a segmentation process to obtain the participant’s silhouettes and a matching process to estimate the pose of the participant. A variable thresholding method was used to extract the silhouettes to solve non-uniform illumination in the recorded swimming video. Prior to the matching process, the human body was modeled as a series of nine segments to help the matching process. The model was then mapped so that it aligned with the silhouettes, which were investigated by similarity of intensity value. To minimize the degree of freedom in image matching, the available joint motion in the swimming human simulation model was used as a priori information for kinematics data of the swimming motion. As a result, the rotation angle’s correlation coefficients between the references and result of the matching process were around 0.95 for trunk, thigh, shank, upper arm, forearm, hand and 0.78 for head, hip and foot. The rotation angle and the velocity of the center of mass were put into the swimming human simulation model for a dynamics analysis. The simulation results show that the velocity obtained in the experiment corresponded to the fluid force exerted on the lower and upper limbs. Consequently, the proposed system of obtaining the joint motion of the butterfly stroke is suitable for daily training and coaching.

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References

  1. Windolf M, Götzen N, Morlock M (2008) Systematic accuracy and precision analysis of video motion capturing systems—exemplified on the Vicon-460 system. J Biomech 41(12):2776–2780

    Article  Google Scholar 

  2. Maletsky LP, Sun J, Morton NA (2007) Accuracy of an optical active-marker system to track the relative motion of rigid bodies. J Biomech 40(3):682–685

    Article  Google Scholar 

  3. Whittle MW (2014) Gait analysis: an introduction. Butterworth-Heinemann, UK

    Google Scholar 

  4. Mihradi S, Ferryanto, Dirgantara T, Mahyuddin AI (2013) Tracking of Markers for 2D and 3D gait analysis using home video cameras. Int J E Health Med Commun (IJEHMC) 4(3):36–52

    Article  Google Scholar 

  5. Monnet T, Samson M, Bernard A, David L, Lacouture P (2014) Measurement of three-dimensional hand kinematics during swimming with a motion capture system: a feasibility study. Sports Eng 17(3):171–181

    Article  Google Scholar 

  6. Corazza S, Muendermann L, Chaudhari AM, Demattio T, Cobelli C, Andriacchi TP (2006) A markerless motion capture system to study musculoskeletal biomechanics: visual hull and simulated annealing approach. Ann Biomed Eng 34(6):1019–1029

    Article  Google Scholar 

  7. Goffredo M, Carter JN, Nixon MS (2009) 2D markerless gait analysis. In: 4th European conference of the international federation for medical and biological engineering, Springer Berlin Heidelberg, pp 67–71

  8. Mündermann L, Corazza S, Andriacchi TP (2010) U.S. Patent No. 7,804,998. U.S. Patent and Trademark Office, Washington, DC

  9. Dubois RP, Thiel DV, James DA (2012) Using image processing for biomechanics measures in swimming. Procedia Eng 34:807–812

    Article  Google Scholar 

  10. Ceseracciu E, Sawacha Z, Fantozzi S, Cortesi M, Gatta G, Corazza S, Cobelli C (2011) Markerless analysis of front crawl swimming. J Biomech 44(12):2236–2242

    Article  Google Scholar 

  11. Nakashima M, Satou K, Miura Y (2007) Development of swimming human simulation model considering rigid body dynamics and unsteady fluid force for whole body. J Fluid Sci Technol 2(1):56–67

    Article  Google Scholar 

  12. Maglischo EW (2003) Swimming fastest. Human Kinetics, Champaign

    Google Scholar 

  13. Moeslund TB, Hilton A, Krüger V (2006) A survey of advances in vision-based human motion capture and analysis. Comput Vis Image Underst 104(2):90–126

    Article  Google Scholar 

  14. Zhang J, Hu J (2008) Image segmentation based on 2D Otsu method with histogram analysis. In: Computer science and software engineering, 2008 international conference on IEEE, vol 6, pp 105–108

  15. Otsu N (1975) A threshold selection method from gray-level histograms. Automatica 11(285–296):23–27

    Google Scholar 

  16. Gonzalez RC, Woods R (2010) Digital image processing. Pearson Education, USA

    Google Scholar 

  17. Nakashima M (2014) Swimming human simulation software “Swumsuit”. http://www.swum.org/swumsuit/index.html. Accessed 19 June 2015

  18. Information-Technology Promotion Agency (2014) Picture materials for education (swimming). http://www2.edu.ipa.go.jp/gz/h1swim/h1kn20/IPA-2kuro-ru.htm. Accessed 19 June 2015

  19. Zitova B, Flusser J (2003) Image registration methods: a survey. Image Vis Comput 21(11):977–1000

    Article  Google Scholar 

  20. Schmidt M (2016) Argmax and Max Calculus [PDF document]. https://www.cs.ubc.ca/~schmidtm/Documents/2016_540_Argmax.pdf. Accessed 26 July 2016

  21. Poli R, Kennedy J, Blackwell T (2007) Particle swarm optimization. Swarm intelligence 1(1):33–57

    Article  Google Scholar 

  22. Kwon YH (1998) DLT method. http://www.kwon3d.com/theory/dlt/dlt.html#dlt. Accessed 14 Mar 2016

Download references

Acknowledgments

The authors gratefully acknowledge the support from the Japan International Cooperation Agency (JICA) for the present study.

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Correspondence to Motomu Nakashima.

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Ferryanto, F., Nakashima, M. Development of a markerless optical motion capture system for daily use of training in swimming. Sports Eng 20, 63–72 (2017). https://doi.org/10.1007/s12283-016-0218-6

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