By Adrian Hilton, Graham Thomas, Thomas B. Moeslund
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Extra resources for Computer Vision in Sports
This approximation makes reconstruction robust against failure to measure 3D ball positions. Two systems were developed based on the new method. A system using two RGB cameras experimentally demonstrated that it could provide accurate information for match analysis. A system using an RGB-D camera was experimentally demonstrated that the system could provide accurate information for service analysis. 1 Introduction There has recently been increasing interest in statistical analysis in sports sciences [1–3].
Dawes R, Weir B, Pike C, Golds P, Mann M, Nicholson M (2012) Enhancing viewer engagement using biomechanical analysis of sport. In: Proceedings of the NEM summit, Istanbul, 16–18 October 2012, pp 121–126. Available as BBC R&D white paper 234. uk/ rd/publications/whitepaper234 19. Sports Video Group (2013) Hybrid aims to cut costs for live sports with automated sport track system. org/main/blog/2013/06/hybrid-aims-to-cut-costs-forlive-sports-with-automated-sport-track-system. Cited 6th April 2014 20.
Org/main/blog/2013/06/hybrid-aims-to-cut-costs-forlive-sports-with-automated-sport-track-system. Cited 6th April 2014 20. Kaiser R, Thler M, Kriechbaum A, Fassold H, Bailer W, Rosner J (2011) Real-time person tracking in high-resolution panoramic video for automated broadcast production. In: Proceedings of 8th European conference on visual media production, 16th November 2011, London, UK 1 Introduction to the Use of Computer Vision in Sports 21 21. Carr P, Mistry M, Matthews I (2013) Hybrid Robotic/virtual Pan-Tilt-Zoom cameras for autonomous event recording.
Computer Vision in Sports by Adrian Hilton, Graham Thomas, Thomas B. Moeslund