Gomez Gabriel, Herrera López Patricia, Link Daniel, Eskofier Bjoern
Digital Sports Group, Pattern Recognition Lab, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.
Departamento de Ingeniería de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain.
PLoS One. 2014 Nov 26;9(11):e111730. doi: 10.1371/journal.pone.0111730. eCollection 2014.
This paper presents methods for the determination of players' positions and contact time points by tracking the players and the ball in beach volleyball videos. Two player tracking methods are compared, a classical particle filter and a rigid grid integral histogram tracker. Due to mutual occlusion of the players and the camera perspective, results are best for the front players, with 74,6% and 82,6% of correctly tracked frames for the particle method and the integral histogram method, respectively. Results suggest an improved robustness against player confusion between different particle sets when tracking with a rigid grid approach. Faster processing and less player confusions make this method superior to the classical particle filter. Two different ball tracking methods are used that detect ball candidates from movement difference images using a background subtraction algorithm. Ball trajectories are estimated and interpolated from parabolic flight equations. The tracking accuracy of the ball is 54,2% for the trajectory growth method and 42,1% for the Hough line detection method. Tracking results of over 90% from the literature could not be confirmed. Ball contact frames were estimated from parabolic trajectory intersection, resulting in 48,9% of correctly estimated ball contact points.
本文介绍了通过跟踪沙滩排球视频中的球员和球来确定球员位置和接触时间点的方法。比较了两种球员跟踪方法,一种是经典粒子滤波器,另一种是刚性网格积分直方图跟踪器。由于球员之间的相互遮挡和摄像机视角问题,对于前排球员的跟踪结果最佳,粒子法和积分直方图法正确跟踪帧的比例分别为74.6%和82.6%。结果表明,使用刚性网格方法跟踪时,在不同粒子集之间对球员混淆的鲁棒性有所提高。更快的处理速度和更少的球员混淆使得这种方法优于经典粒子滤波器。使用了两种不同的球跟踪方法,它们使用背景减法算法从运动差异图像中检测球候选物。根据抛物线飞行方程估计并内插球的轨迹。轨迹增长法对球的跟踪准确率为54.2%,霍夫线检测法为42.1%。无法证实文献中超过90%的跟踪结果。通过抛物线轨迹相交估计球接触帧,正确估计的球接触点比例为48.9%。