Abstract
This initial research presents the multiview human body tracking method as a tool to measure hurdle clearance parameters. This study was conducted on high level hurdlers, who were members of the Polish national team. The video sequences were recorded by a multicamera system consisting of three 100 Hz Full HD cameras. The sequences were registered under the simulated starting conditions of a 110 m hurdles race. Kinematic parameters were estimated based on the analysis of images from the multicamera system. These parameters were compared with the parameters obtained from ground truth poses. Mean absolute error and mean relative error were selected as the quality criteria. The main advantage of the method presented here is that it does not need any special clothes, markers or the support of other estimation techniques.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Iskra, J.: Scientific research in hurdle races. AWF Katowice (2012)
Čoh, M.: Biomechanical analysis of Colin Jackson’s hurdle clearance technique. New Studi. Athletics 1, 33–40 (2003)
Čoh, M., Dolenec, A., Tomažin, K., Zvan, M.: Dynamic and kinematic analysis of the hurdle clearance technique. In: Čoh, M. (ed.) Biomechanical Diagnostic Methods in Athletic Training. University of Ljubljana, pp. 109–116 (2008)
Salo, A., Grimshaw, P.N., Marar, L.: 3-D biomechanical analysis of sprint hurdles at different competitive levels. Med. Sci. Sports Exerc. 29, 231–237 (1997)
Reyes, C.E., Mojica, E.F., Correa, C.V., Arguello, H.: Algorithm for underwater swimmer tracking using the HSV color model and compressive sensing. In: 2016 IEEE Colombian Conference on Communications and Computing (COLCOM), pp. 1–5 (2016)
Ramasso, E., Panagiotakis, C., Rombaut, M., Pellerin, D., Tziritas, G.: Human shape-motion analysis in athletics videos for coarse to fine action/activity recognition using transferable belief model. Electron. Lett. Comput. Vis. Image Anal. 7, 32–50 (2009)
Panagiotakis, C., Grinias, I., Tziritas, G.: Automatic human motion analysis and action recognition in athletics videos. In: 14th European Signal Processing Conference, pp. 1–5 (2006)
Perš, J., Kovacic, S.: A system for tracking players in sports games by computer vision. Elektrotehniški vestnik 67, 281–288 (2000)
Kwon, J., Kim, K., Cho, K.: Multi-target tracking by enhancing the kernelised correlation filter-based tracker. Electron. Lett. 53, 1358–1360 (2017)
Kim, Y., Cho, K.S.: Robust multi-object tracking to acquire object oriented videos in indoor sports. In: 2016 International Conference on Information and Communication Technology Convergence (ICTC), pp. 1104–1107 (2016)
Manafifard, M., Ebadi, H., Moghaddam, H.A.: Appearance-based multiple hypothesis tracking: application to soccer broadcast videos analysis. Sig. Process.: Image Commun. 55, 157–170 (2017)
Yang, Y., Li, D.: Robust player detection and tracking in broadcast soccer video based on enhanced particle filter. J. Vis. Commun. Image Represent. 46, 81–94 (2017)
Elliott, N., Choppin, S., Goodwill, S.R., Allen, T.: Markerless tracking of tennis racket motion using a camera. Procedia Eng. 72, 344–349 (2014). The Engineering of Sport 10
Sheets, A.L., Abrams, G.D., Corazza, S., Safran, M.R., Andriacchi, T.P.: Kinematics differences between the flat, kick, and slice serves measured using a markerless motion capture method. Ann. Biomed. Eng. 39, 3011–3020 (2011)
Hamatani, T., Sakaguchi, Y., Uchiyama, A., Higashino, T.: Player identification by motion features in sport videos using wearable sensors. In: 2016 Ninth International Conference on Mobile Computing and Ubiquitous Networking (ICMU), pp. 1–6 (2016)
Cheng, F., Christmas, W., Kittler, J.: Periodic human motion description for sports video databases. In: Proceedings of the Pattern Recognition, 17th International Conference on ICPR 2004, vol. 3, pp. 870–873. IEEE Computer Society, Washington, DC (2004)
Zhang, Y., Feng, S., Sun, X., Yang, H.: Research on tracking algorithm for fast-moving target in sport video. J. Comput. Theor. Nanosci. 14, 230–236 (2017)
Krzeszowski, T., Przednowek, K., Wiktorowicz, K., Iskra, J.: Multiview human body tracking of hurdle clearance: a case study. In: Proceedings of the 5th International Congress on Sport Sciences Research and Technology Support, vol. 1, pp. 83–88. icSPORTS, INSTICC, SciTePress (2017)
John, V., Trucco, E., Ivekovic, S.: Markerless human articulated tracking using hierarchical particle swarm optimisation. Image Vis. Comput. 28, 1530–1547 (2010)
Kwolek, B., Krzeszowski, T., Gagalowicz, A., Wojciechowski, K., Josinski, H.: Real-time multi-view human motion tracking using particle swarm optimization with resampling. In: Perales, F.J., Fisher, R.B., Moeslund, T.B. (eds.) AMDO 2012. LNCS, vol. 7378, pp. 92–101. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31567-1_9
Deutscher, J., Reid, I.: Articulated body motion capture by stochastic search. Int. J. Comput. Vision 61, 185–205 (2005)
Krzeszowski, T., Przednowek, K., Wiktorowicz, K., Iskra, J.: Estimation of hurdle clearance parameters using a monocular human motion tracking method. Comput. Methods Biomech. Biomed. Eng. 19, 1319–1329 (2016). PMID: 26838547
Sidenbladh, H., Black, M.J., Fleet, D.J.: Stochastic tracking of 3D human figures using 2D image motion. In: Vernon, D. (ed.) ECCV 2000. LNCS, vol. 1843, pp. 702–718. Springer, Heidelberg (2000). https://doi.org/10.1007/3-540-45053-X_45
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, vol. 4, pp. 1942–1948. IEEE Press, Piscataway (1995)
Tsai, R.: A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE J. Robot. Autom. 3, 323–344 (1987)
Acknowledgements
This work has been partially supported by the Polish Ministry of Science and Higher Education within the research project “Development of Academic Sport” in the years 2016-2018, project No. N RSA4 00554.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Krzeszowski, T., Przednowek, K., Wiktorowicz, K., Iskra, J. (2019). The Application of Multiview Human Body Tracking on the Example of Hurdle Clearance. In: Cabri, J., Pezarat-Correia, P., Vilas-Boas, J. (eds) Sport Science Research and Technology Support. icSPORTS icSPORTS 2016 2017. Communications in Computer and Information Science, vol 975. Springer, Cham. https://doi.org/10.1007/978-3-030-14526-2_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-14526-2_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-14525-5
Online ISBN: 978-3-030-14526-2
eBook Packages: Computer ScienceComputer Science (R0)