Motion Prejudgment Dependent Mixture System Noise in System Model for Tennis Ball 3D Position Tracking by Particle Filter
Motion Prejudgment Dependent Mixture System Noise in System Model for Tennis Ball 3D Position Tracking by Particle Filter
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DOI：
10.1109/scis-isis.2016.0038
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发表时间：
2016-12
期刊：
影响因子：
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通讯作者：
Y. Wang;Xina Cheng;N. Ikoma;M. Honda;T. Ikenaga
中科院分区：
文献类型：
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作者：
Y. Wang;Xina Cheng;N. Ikoma;M. Honda;T. Ikenaga
在网球比赛分析中，球的三维位置对判分和球员评价起着至关重要的作用。在三维空间中对网球进行跟踪时，网球运动速度快、运动变化突然是网球运动轨迹难以预测的主要问题。针对上述两个问题，我们提出了一种基于精细混合系统噪声的系统模型。混合系统噪声包括一般变化噪声和依赖于网球运动预判结果的自适应突变噪声。运动预判方法是根据球和球员的当前状态来进行的。球的运动分为一般运动和三种突然运动，包括扣杀、反弹和击球。实验基于13个高清电视视频序列，这些视频序列由位于阴天室外网球场四个角落的四个摄像机记录，其中包括两名球员，以探索所提出方法的性能。跟踪成功率为81.14%，较常规工作提高27.64%。
In tennis game analysis, the 3D position of ball plays a crucial role in score judgment and player evaluation. When tracking the tennis ball in 3D space, high speed and abrupt motion change of the tennis ball are the main problems which make it difficult to predict the near future course of the ball. Aiming at solving above two problems, we propose a system model based on an elaborated mixture system noise. The mixture system noise consists of general change noise and adaptive abrupt change noise which is dependent on motion prejudgment result of tennis ball. The motion prejudgment method is carried out by the current state of ball and players. The motion of ball is classified into general motion and three abrupt motions, including smash, bounce and hit the net. Experiments based on 13 HDTV video sequences, which were recorded by four cameras located at four corners of the tennis court outside in a cloudy day including two players were used to explore the performance of the proposed method. The tracking success rate is 81.14%, gaining 27.64% improvement compared with conventional work.