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Construction of an Intelligent Tennis Coach Based on Kinect and a Sensor-Based Tennis Racket

机译:基于Kinect和基于传感器的网球拍的智能网球教练的构建

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The purpose of this paper is to develop an artificial intelligence coach system which can be used to provide beginners a more economical way to learn tennis and to achieve as similar as the coach to guide the training. To reach the goal, artificial intelligence coach system is composed of three phases that are (1) Tennis swing motion data collection, (2) CAST-based swing motion group construction, and (3) Online tennis swing motion analysis. In the first phase, the tennis motions are collected using the Kinect and the built sensor-based tennis racket. Then, the cluster affinity search technique (CAST) and the dynamic time warping (DTW) are utilized to divide the collected swing motion series data into groups to form swing motion groups. In the third phase, using the swing motion groups, the system can provide possible tennis motion improvement suggestions. At last, experiments were also conducted on the real dataset to show the effectiveness of the proposed system.
机译:本文的目的是开发一种人工智能教练系统,该系统可为初学者提供一种更经济的学习网球的方法,并获得与指导教练类似的教练。为了实现该目标,人工智能教练系统由三个阶段组成:(1)网球挥拍动作数据收集,(2)基于CAST的挥拍动作组构建,以及(3)在线网球挥拍动作分析。在第一阶段,使用Kinect和内置的基于传感器的网球拍来收集网球运动。然后,利用聚类亲和力搜索技术(CAST)和动态时间规整(DTW)将收集的挥杆运动序列数据划分为组,以形成挥杆运动组。在第三阶段,使用挥杆动作组,系统可以提供可能的网球动作改进建议。最后,还对真实数据集进行了实验,以证明所提出系统的有效性。

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