Abstract
This paper proposes a volleyball trajectory tracking method adapting to occlusion scenes. Firstly, the target volleyball is obtained in the video manually and the Kalman filter algorithm combined with Continuously Adaptive Mean Shift (CAMSHIFT) algorithm is used to track and determine the size and position of the volleyball in each frame of video, and then it is determined whether there exists an occlusion. If there is no occlusion, positions of the volleyball in each frame of video are connected to obtain the trajectory of the volleyball. If there is occlusion, the Kalman filter algorithm is used to predict the positions of the volleyball in the occlusion section, and the size remains unchanged. Finally, the positions of the volleyball in each frame of video is connected to a line to obtain the trajectory of the volleyball motion. The proposed approach solves the problem of more complicated video background in volleyball movement. When the volleyball is blocked, it can accurately predict the volleyball movement trajectory so as to accurately track the volleyball movement trajectory under dynamic and occlusion scenes.
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Acknowledgment
This work has applied for a China National Invention Patent (NO: 201710981725.7) and has been supported by the Ministry of Education’s Higher Education Department’s Industry-Science Collaborative Education Innovation Fund (201601030018).
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Yu, T., Hu, Z., Liu, X., Jiang, P., Xie, J., Zang, T. (2018). A Volleyball Movement Trajectory Tracking Method Adapting to Occlusion Scenes. In: Zhou, Q., Gan, Y., Jing, W., Song, X., Wang, Y., Lu, Z. (eds) Data Science. ICPCSEE 2018. Communications in Computer and Information Science, vol 901. Springer, Singapore. https://doi.org/10.1007/978-981-13-2203-7_62
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DOI: https://doi.org/10.1007/978-981-13-2203-7_62
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