Athletes Tracking using Homography Method: a Preliminary Study

 
 
 
  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract


    Particle tracking has been used widely to track a single particle motion or trajectory in a medium. One of the applications of the particle tracking is in sports analysis. The tracking method can be divided into, the wearable device based system and the image based system. The wearable device based system utilizing global (GPS) and local (LPM) positioning system to track player movement. The image based system use video image processing to track the player movement and recorded is frames basis. However, the image processing method in a football match requires correction as it is normally recorded from the side of the field. Thus, to solve this problem a set of mathematical solution is needed to convert the image coordinate system (pixels) to the actual coordinate system (meters). The most commonly used is the homography method. The technique requires at least 4 reference points to transform the image coordinate into the actual coordinate system. In this project, a futsal game was recorded. The image coordinate of the player were marked in each frame with respect to the time. The image coordinate data were converted into the actual coordinate using homography matrix. Comparisons were made between the homography technique method and open-source available image warp processing method for validation. Based on the result, the homography coordinate transformation system produce a good agreement with actual player activity on the field.

     

     


  • Keywords


    Planar transformation, Homography matrix, Image perspective

  • References


      [1] J. Gudmundsson and T. Wolle, “Football analysis using spatio-temporal tools”, Comput. Environ. Urban Syst. Vol. 47, (2014), pp. 16–27.

      [2] C. Carling, J. Bloomfield, L. Nelsen, and T. Reilly, “The role of motion analysis in elite soccer”, Sport. Med. Vol. 38, No. 10, (2008) pp. 839–862.

      [3] M. Siegle, T. Stevens, and M. Lames, “Design of an accuracy study for position detection in football”, J. Sports Sci. Vol. 31, (2012), pp. 1–7.

      [4] P. Figueroa, N. Leite, R. M. L. Barros, I. Cohen and G. Medioni, “Tracking soccer players using the graph representation”, Proceedings of the International Conference on Pattern Recognition 4, (2004), pp. 787-790.

      [5] M. S. Couceiro, F. M. Clemente, and F. M. L. Martins, “Analysis of football player’s motion in view of fractional calculus”, Cent. Eur. J. Phys. Vol. 11, No. 6, (2013), pp. 714–723.

      [6] R. Hartley , A. Zisserman , Multiple View Geometry in Computer Vision, 2nd ed., Cambridge University Press, (2003), pp. 88-92.

      [7] Z. Niu, X. Gao, and Q. Tian, “Tactic analysis based on real-world ball trajectory in soccer video”, Pattern Recognit. Vol. 45, No. 5, (2012), pp. 1937–1947.

      [8] P. Chen and D. Suter, “Error analysis in homography estimation by first order approximation tools: A general technique”, J. Math. Imaging Vis. Vol. 33, No. 3, (2009) pp. 281–295.

      [9] J. Mrovlje, and D. VranCic, "Distortion impact on a stereo distance", in Proc. of the 10th International PhD Workshop on Systems and Control: young generation viewpoint, (2009).

      [10] M. Alemán-Flores, L. Alvarez, L. Gomez, P. Henriquez, and L. Mazorra, “Camera calibration in sport event scenarios”, Pattern Recognit. Vol. 47, No. 1, (2014), pp. 89–95.

      [11] F. E. E. Devernay and O. Faugeras, “Straight lines have to be straight: automatic calibration and removal of distortion from scenes of structured enviroments”, Mach. Vis. Appl. Vol. 13, No 1, (2001), pp. 14–24.

      [12] S. Y. Park and G. G. Park, “Active calibration of camera-projector systems based on planar homography”, Proceedings of the International Conference on Pattern Recognition, (2010), pp. 320-323.

      [13] D. P. Wong, V. Pialoux, C. Hautier, K. Chamari, and A. Dellal, “Physical activity during a prolonged congested period in a top class European football team”, Asian J Sports Med. Vol. 5, No. 1, (2014), pp. 47–53.

      [14] J. Mara,S. Morgan, K. Pumpa, and K. Thompson, “The Accuracy and Reliability of a New Optical Player Tracking System for Measuring Displacement of Soccer Players”, International Journal of Computer Science in Sport, Vol. 16, No. 3, (2017), pp. 175-184.


 

View

Download

Article ID: 22427
 
DOI: 10.14419/ijet.v7i4.27.22427




Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.