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Current Directions in Biomedical Engineering

Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering

Editor-in-Chief: Dössel, Olaf

Editorial Board: Augat, Peter / Buzug, Thorsten M. / Haueisen, Jens / Jockenhoevel, Stefan / Knaup-Gregori, Petra / Kraft, Marc / Lenarz, Thomas / Leonhardt, Steffen / Malberg, Hagen / Penzel, Thomas / Plank, Gernot / Radermacher, Klaus M. / Schkommodau, Erik / Stieglitz, Thomas / Urban, Gerald A.

CiteScore 2018: 0.47

Source Normalized Impact per Paper (SNIP) 2018: 0.377

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Towards a better understanding of the overall health impact of the game of squash: automatic and high-resolution motion analysis from a single camera view

Christopher Brumann
  • Corresponding author
  • University of Applied Sciences and Arts Dortmund, Dept. of Computer Science, Dortmund, Germany
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/ Markus Kukuk
  • University of Applied Sciences and Arts Dortmund, Dept. of Computer Science, Dortmund, Germany
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2017-09-07 | DOI: https://doi.org/10.1515/cdbme-2017-0189


In this paper, we present a method for locating and tracking players in the game of squash using Gaussian mixture model background subtraction and agglomerative contour clustering from a calibrated single camera view. Furthermore, we describe a method for player re-identification after near total occlusion, based on stored color- and region-descriptors. For camera calibration, no additional pattern is needed, as the squash court itself can serve as a 3D calibration object. In order to exclude non-rally situations from motion analysis, we further classify each video frame into game phases using a multilayer perceptron. By considering a player’s position as well as the current game phase we are able to visualize player-individual motion patterns expressed as court coverage using pseudo colored heat-maps. In total, we analyzed two matches (six games, 1:28h) of high quality commercial videos used in sports broadcasting and compute high resolution (1cm per pixel) heat-maps. 130184 manually labeled frames (game phases and player identification) show an identification correctness of 79.28±8.99% (mean±std). Game phase classification is correct in 60.87±7.62% and the heat-map visualization correctness is 72.47±7.27%.

Keywords: squash; player detection; player identification; motion analysis; heat map

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Published Online: 2017-09-07

Citation Information: Current Directions in Biomedical Engineering, Volume 3, Issue 2, Pages 819–823, ISSN (Online) 2364-5504, DOI: https://doi.org/10.1515/cdbme-2017-0189.

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©2017 Christopher Brumann et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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