Player Tracking using Multi-viewpoint Images in Basketball Analysis
Player Tracking using Multi-viewpoint Images in Basketball Analysis
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DOI：
10.5220/0009097408130820
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Shuji Tanikawa;N. Tagawa
中科院分区：
文献类型：
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作者：
Shuji Tanikawa;N. Tagawa
本研究的目的是利用多视点图像，通过避免球员遮挡来实现对篮球运动员的自动跟踪，这是篮球视频分析中的一个重要问题。使用手持相机拍摄的图像，将应用范围扩大到学校俱乐部活动等用途。通过将每个摄像机图像的球员跟踪结果与从球场上方观看的二维地图相结合，使用投影变换，利用来自其他摄像机的信息稳定地解决了由一个摄像机引起的遮挡问题。此外，使用OpenPose进行播放器检测可减少在整合所有相机图像之前在每个相机图像中发生的遮挡。通过对真实图像序列的实验，我们证实了该方法的有效性。fi。
: In this study, we aim to realize the automatic tracking of basketball players by avoiding occlusion of players, which is an important issue in basketball video analysis, using multi-viewpoint images. Images taken with a hand-held camera are used, to expand the scope of application to uses such as school club activities. By integrating the player tracking results from each camera image with a 2-D map viewed from above the court, using projective transformation, the occlusion caused by one camera is stably solved using the information from other cameras. In addition, using OpenPose for player detection reduces the occlusion that occurs in each camera image before all camera images are integrated. We confirm the effectiveness of our method by experiments with real image sequences.