Ball event recognition using hmm for automatic tennis annotation
Ball event recognition using hmm for automatic tennis annotation
复制标题
使用 hmm 进行球事件识别以进行自动网球注释
DOI：
10.1109/icip.2010.5652415
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
Aftab Khan
中科院分区：
文献类型：
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作者：
I. Almajai;J. Kittler;T. D. Campos;W. Christmas;F. Yan;David Windridge;Aftab Khan
自动视频索引和摘要的一个关键先决条件是事件和动作的描述。在许多运动中，球和代理人的运动在描述事件中起着至关重要的作用。然而，文献中针对网球事件识别问题的唯一现有解决方案是[8]中的工作，它依赖于一组启发式规则，例如球与运动员或球场线之间的接近度来对候选球事件进行分类。我们提出隐马尔可夫模型（HMM）范例来自动学习从球轨迹中识别事件，并证明其捕获球运动动态的能力可以带来更高的性能。
A key prerequisite of automatic video indexing and summarisation is the description of events and actions. In the context of many sports, the motion of the ball and agents plays an essential role in describing events. However, the only existing solution for the tennis event recognition problem in the literature is the work in [8] which relies on a set of heuristic rules such as proximity between ball and players or court lines to classify ball event candidates. We present hidden Markov models (HMMs) paradigm to automatically learn to identify events from ball trajectories and demonstrate that its ability to capture the dynamics of the ball movement lead to a much higher performance.