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
Method of improved YOLOV7 based multitarget tracking for overlapping regions in variable scale networks
在实际场景中,目标之间常常存在重叠或部分遮挡的情况,若是未进行有效的多目标检测以及了解变规模网络重叠区域内的节点状况,会导致目标跟踪精度下降.对此,提出一种基于改进YOLOV7的变规模网络重叠区域多目标跟踪方法.首先,采用改进YOLOV7对变规模网络重叠区域多目标进行检测;然后,在目标检测的基础上,对多目标轨迹特征进行提取;最后,基于提取到的多目标轨迹特征,已知目标的速度、方向与距离,实现变规模网络重叠区域的多目标跟踪.实验结果表明,所提方法的跟…查看全部>>
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 …查看全部>>
王博;柴锐
中北大学 计算机科学与技术学院,山西 太原 030051中北大学 计算机科学与技术学院,山西 太原 030051
电子信息工程
多目标跟踪重叠区域YOLOV7多目标检测轨迹特征提取曼哈顿距离
multitarget trackingoverlapping regionsYOLOV7multitarget detectiontrajectory feature extractionManhattan distance
《现代电子技术》 2024 (12)
57-61,5
山西省科技厅一般面上项目:基于视觉辅助计算的多模态CT联合SPECT功能成像分析对肾脏占位病变的诊断价值研究(20210302123033)
评论