基于改进YOLOV7的变规模网络重叠区域多目标跟踪方法OA北大核心CSTPCD

In practical scenarios,there is often overlap or partial occlusion between targets.If effective multitarget detection is not carried out to understand the node status in the overlapping area of the variable scale network,it will lead to a decrease in target tracking accuracy.Therefore,an improved YOLOV7 based multi target tracking method for the overlapping area of the variable scale network is proposed.The improved YOLOV7 is used to detect multiple targets in overlapping areas of the variable scale network.On the basis of target detection,multi target trajectory features are extracted.Multitarget tracking for overlapping areas in the variable scale network is realized based on the extracted multitarget trajectory features,and the given speed,direction,and distance of the targets.The experimental results show that the proposed method has a tracking accuracy of up to 98%,and the Manhattan distance is significantly smaller than that of the comparison method,only between 0.1 and-0.1,which has better performance and practicality.