计算机科学 ›› 2021, Vol. 48 ›› Issue (11A): 340-344.doi: 10.11896/jsjkx.210200004
叶阳, 卢奇, 程时伟
YE Yang, LU Qi, CHENG Shi-wei
摘要： 车辆目标跟踪是实现车联网不可或缺的一环,旨在获取车辆的动态信息,以提高交通运行效率。其核心是对大量监控探头采集的视频图像进行分析处理,实现车辆的实时检测与跟踪。为了进一步提高目标检测效率,降低硬件成本,文中提出了基于二帧差分法的前景检测方法,以及基于质心法的车辆轮廓检测与跟踪方法。基于OpenCV3.4.1和VS2017进行验证实验和仿真测试,结果表明,该算法对车辆跟踪的精确率达到89.1%,平均处理耗时42.63 ms,具有较好的实时性和鲁棒性,可在车联网嵌入式设备上进行部署和应用。
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