基于特征点轨迹的多目标跟踪算法

A multi-target tracking algorithm based on feature point trajectories

在连续的视频流中,多目标跟踪的任务就是在每一帧中确定目标物体的位置,但是跟踪算法会受到很多外界因素干扰,其中遮挡对跟踪效果的干扰最为严重,为此提出基于特征点轨迹的跟踪算法,用于解决多目标相互遮挡时的跟踪难题.首先跟踪时引入延迟,在处理当前帧时提前获取未来的N帧图像;再提取图像上的特征点并串联成轨迹,根据轨迹来估计目标在N帧之后的位置.根据目标的位置分析目标的运动,从而定位当前帧目标的位置.实验数据表明,这种方法能够有效处理目标遮挡,并且该算法的复杂度比很多传统算法都低,能够在低端处理器上实时运行,满足实际需求.

In a continuous video stream,the multi-target tracking task is to determine the positions of the concerned targets in each frame.However,the tracking algorithm suffer from many challenging issues,such as appearance variation,lighting change,occlusion and cluttered background.Especially,occlusion has the most negative impact on tracking performance.Therefore,a tracking algorithm is proposed based on feature point trajectory to solve the tracking problem where multiple targets may occlude each other.The main idea of the proposed tracking algorithm is to introduce the delay during tracking,and acquire future N frame images in advance when processing the current frame;extract feature points from the obtained frame images and connect them to form feature trajectories,and estimate the positions of targets after N frames according to the obtained trajectories.After predicting the future positions of the targets,the motion of targets can be analyzed so as to precisely determine their locations at the current frame.Experiments show the this algorithm can effectively deal with occlusion.Moreover,the complexity of the proposed algorithm is lower than that of many traditional algorithms,which guarantees real-time tracking on the low-end processor in actual applications.