基于KCF跟踪算法的目标轨迹记录系统

为了确保跟踪算法能够实时跟踪上高速移动的目标并且记录目标的三维坐标.本系统使用了一种基于KCF（Kernelized Correlation Filters）的高速跟踪算法来保证系统能够跟踪到移动速度较快的目标.首先，使用KCF跟踪算法来跟踪目标；然后，利用ORB特征点检测来计算目标特征点从而找到多摄像机中对应的点，找到对应点之后利用多摄像机的三维重建原理计算出每一帧中目标物体的三维坐标点；最后，用多项式对每一帧运动轨迹的离散点进行拟合得到最终的运行轨迹.实验结果证明该算法能够有效跟踪目标，整个系统能够满足实际的需求.

Target Track Recording System Based on Kernelized Correlation Filters Tracking Algorithm

In order to ensure that our tracking algorithm can real-time capture the fast-moving target and record its three-dimensional coordinates, the system uses a high-speed tracking algorithm based on Kernelized Correlation Filters (KCF). First, use KCF tracking algorithm to track the target. Second, use ORB feature point detection algorithm to calculate the target feature point. Then find out the corresponding point in Multi-Camera. After finding the corresponding points, use three-dimensional reconstruction theory of Multi-Camera to calculate the three-dimensional coordinates of the target object in each frame. Finally, using polynomial to fit the discrete points of each frame and then get the final trajectory. The experimental results show that this algorithm can track target efficiently and the whole system can meet actual requirements.