Abstract
Ball and player detection in Broadcast Tennis Video (BTV) is a critical and challenging task in tennis video semantic analysis. Informally, the challenges are due to the camera motion and the other causes such as the small size of the tennis ball and many objects resembles the ball and considering the player, the human body along with the tennis racket is not detected completely. In this paper, it is proposed an improved object detection technique in BTV. In order to detect the ball, logical AND operation is applied between the created background and image difference is performed, from that ball candidates are detected by applying threshold values and dilated. Player detection is performed from AND results by finding the biggest blob and filling the whole detected object by removing the small one. The experimental result shows that the proposed approach achieved the higher accuracy in object identification, their object the landing frames and positions. It is achieved a high hit rate and less fail rate.
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Archana, M., Kalaiselvi Geetha, M. (2016). An Efficient Ball and Player Detection in Broadcast Tennis Video. In: Berretti, S., Thampi, S., Srivastava, P. (eds) Intelligent Systems Technologies and Applications. Advances in Intelligent Systems and Computing, vol 384. Springer, Cham. https://doi.org/10.1007/978-3-319-23036-8_37
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DOI: https://doi.org/10.1007/978-3-319-23036-8_37
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