Abstract
The article presents the steps required to reconstruct a 3D trajectory of a golf ball flight, bounces and roll in short game. Two video cameras were used to capture the last parts of the trajectories including the bounces and roll. Each video sequence is processed and the ball is detected and tracked until is stops. Detected positions from both video sequences are then matched and 3D trajectory is obtained and presented as an X3D model.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Urtasun, R., Fleet, D.J., Fua, P.: Monocular 3D Tracking of the Golf Swing. Computer Vision and Pattern Recognition 2, 932–938 (2005)
Woodward, A., Delmas, P.: Computer Vision for Low Cost 3-D Golf Ball and Club Tracking. In: Proc. Image and Vision Computing, New Zealand (2005)
Owens, N., Harris, C., Stennett, C.: Hawk-eye Tennis System. In: International Conference on Visual Information Engineering, pp. 182–185 (2003)
Pingali, G., Opalach, A., Jean, Y.: Ball Tracking and Virtual Replays for Innovative Tennis Broadcasts. In: 15th International Conference on Pattern Recognition, vol. 4, pp. 152–156 (2000)
Yu, X., Leong, H.W., Xu, C., Tian, Q.: Trajectory-Based Ball Detection and Tracking in Broadcast Soccer Video. IEEE Transactions on Multimedia 8(6), 1164–1178 (2006)
Ren, J., Orwell, J., Jones, G.A., Xu, M.: Tracking the soccer ball using multiple fixed cameras. Computer Vision and Image Understanding (in press)
Chien, S., Ma, S., Chen, L.: Efficient Moving Object Segmentation Algorithm Using Background Registration Technique. IEEE Transactions on Circuits and Systems for Video Technology 12(7), 577–586 (2002)
Petrie, T.: Tracking Bouncing Balls Using Kalman Filters and Condensation, http://www.marcad.com/cs584/Tracking.html
Maybeck, P.S.: Stochastic models, estimation and control, vol. 1. Academic Press, London (1979)
Bouguet, J.-Y.: Camera Calibration Toolbox for Matlab, http://www.vision.caltech.edu/bouguetj/calib_doc/
Kovesi, P.D.: MATLAB and Octave Functions for Computer Vision and Image Processing. School of Computer Science & Software Engineering, The University of Western Australia, http://www.csse.uwa.edu.au/~pk/research/matlabfns/
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2003)
Wikipedia: Hat operator, http://en.wikipedia.org/wiki/Hat_operator
Ma, Y., Soatto, S., Košecká, J., Sastry, S.S.: An Invitation to 3-D Vision. Springer, Heidelberg (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zupančič, T., Jaklič, A. (2009). Automatic Golf Ball Trajectory Reconstruction and Visualization. In: Gagalowicz, A., Philips, W. (eds) Computer Vision/Computer Graphics CollaborationTechniques. MIRAGE 2009. Lecture Notes in Computer Science, vol 5496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01811-4_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-01811-4_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01810-7
Online ISBN: 978-3-642-01811-4
eBook Packages: Computer ScienceComputer Science (R0)