By Adrian Hilton, Graham Thomas, Thomas B. Moeslund
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Extra resources for Computer Vision in Sports
In: CVPR, pp 260–265 23. Pingali GS, Opalach A, Jean Y (2000) Ball tracking and virtual replays for innovative tennis broadcasts. In: ICPR, pp 4152–4156 24. Streit R, Luginbuhl T (1995) Probabilistic multi-hypothesis tracking. Technical Report 25. uk 26. Tordoff BJ, Murray DW (2005) Guided-MLESAC: faster image transform estimation by using matching priors. PAMI 27(10):1523–1535 27. Torr PHS, Zisserman A (2000) MLESAC: a new robust estimator with application to estimating image geometry. Comput Vis Image Underst 78:138–156 28.
7]. We developed a system using two RGB cameras based on the new method. The system obtains shot data for match analysis and is expected to solve the problem with conventional analysis. We then developed a system using an RGB-D camera to optimize usability for practitioners. Although the system using the RGB-D camera cannot reconstruct the trajectories of fast-moving or rotating balls due to functional issues with the RGB-D camera, the system is still useful for analyzing services. Moreover, we expect that the system would be able to reconstruct the positions of any balls in the future when the frame rates and the measurement range of depths of RGB-D cameras were enhanced.
Reusens M, Vetterli M, Ayer S, Bergnozoli V (2007) Coordination and combination of video sequences with spatial and temporal normalization. European patent specification EP1247255A4, 2007 15. Grau O, Price M, Thomas G (2001) Use of 3-D techniques for virtual production. In: SPIE conference on videometrics and optical methods for 3D shape measurement, San Jose, USA, January 2001. Available as BBC R&D white paper 033. shtml 16. Red Bee Media (2014) The Piero™Sports Graphics System. com/ piero. Cited 6th April 2014 17.