Anti-occlusion observation model and automatic recovery for multi-view ball tracking in sports analysis
Anti-occlusion observation model and automatic recovery for multi-view ball tracking in sports analysis
复制标题
运动分析中多视角球跟踪的抗遮挡观测模型及自动恢复
DOI：
10.1109/icassp.2016.7471927
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
T. Ikenaga
中科院分区：
文献类型：
--
作者：
Xina Cheng;M. Honda;N. Ikoma;T. Ikenaga
球的3D位置在专业运动分析中起着至关重要的作用。在球类运动中，对球的精确位置的精确跟踪有着很高的要求，而球的三维坐标不精确和遮挡问题影响着跟踪的性能。本文提出了一种基于多视点视频的防遮挡观察模型和三维球检测自动恢复算法，实现了对球在三维空间中的跟踪。抗遮挡观察模型评估每个摄像机的图像，并消除其中的球被遮挡的摄像机的影响。自动恢复方法利用多路视频的单应性关系来检测球的三维位置，并在检测到跟踪失败时产生新的分布来启动跟踪器。实验结果表明，基于HDTV视频序列，这是由四个摄像机位于球场的角落拍摄，三维球跟踪的成功率达到99.14%。
The 3D position of the ball plays a crucial role in professional sport analysis. In ball sports, tracking of ball's precise position accurately is highly required, whose performance is affected by inaccurate 3D coordinates and occlusion problem. In this paper, we propose anti-occlusion observation model and automatic recovery by 3D ball detection based on multiview videos to track the ball in 3D space. The anti-occlusion observation model evaluates each camera's image and eliminates the influence of the cameras in which the ball is occluded. The automatic recovery method detects the ball's 3D position by homography relation of the multi-video and generates a new distribution to initiate the tracker when tracking failure is detected. Experimental results based on the HDTV video sequences, which were captured by four cameras located at the corners of the court, show that the success rate of the 3D ball tracking achieves 99.14%.