基于YOLOv3和ASMS的目标跟踪算法

为了解决传统算法在全自动跟踪过程中遇到遮挡或运动速度过快时的目标丢失问题,本文提出一种基于YOLOv3和ASMS的目标跟踪算法。首先通过YOLOv3算法进行目标检测并确定跟踪的初始目标区域,然后基于ASMS算法进行跟踪,实时检测并判断目标跟踪效果,通过二次拟合定位和YOLOv3算法实现跟踪目标丢失后的重新定位。为了进一步提升算法运行效率,本文应用增量剪枝方法,对算法模型进行了压缩。通过与当前主流算法进行对比,实验结果表明,本算法能够很好地解决受到遮挡时跟踪目标的丢失问题,提高了目标检测和跟踪的精度,且具有计算复杂度低、耗时少,实时性高的优点。

Target tracking algorithm based on YOLOv3 and ASMS

In order to solve the problem of loss when the target encounters occlusion or the speed is too fast during the automatic tracking process,a target tracking algorithm based on YOLOv3 and ASMS is proposed.Firstly,the target is detected by the YOLOv3 algorithm and the initial target area to be tracked is determined.After that,the ASMS algorithm is used for tracking.The tracking effect of the target is detected and judged in real time.Repositioning is achieved by quadratic fitting positioning and the YOLOv3 algorithm when the target is lost.Finally,in order to further improve the efficiency of the algorithm,the incremental pruning method is used to compress the algorithm model.Compared with the mainstream algorithms,experimental results show that the proposed algorithm can solve the lost problem when the tracking target is occluded,improving the accuracy of target detection and tracking.It also has advantages of low computational complexity,time-consuming,and high real-time performance.