摘要
针对传统的行人检测与跟踪算法检测跟踪效果差以及速度慢的问题,提出一种快速行人检测跟踪方法。首先采用ViBe算法快速检测出运动区域,快速检测定位行人候选区;然后采用HOG+SVM行人检测器检测出运动目标候选区的行人;最后利用Kalman滤波算法对行人目标进行跟踪。此外,为了减少误检率,在样本训练阶段通过增加困难样本进行SVM二次训练。实验结果表明本文提出行人检测跟踪算法在视频序列中具有良好的鲁棒性,其检测性能明显提高。
An fast pedestrian detection and tracking method is proposed to deal with the problems of slowly detection and poor tracking effect in traditional pedestrian detection and tracking method.Firstly,the ViBe algorithm is used to quickly extract the motion area,namely the pedestrian candidate area.Then the HOG+SVM pedestrian detector is used to detect the pedestrian in the candidate zone of moving target.Finally,Finally,Kalman filter is used to track the pedestrian target.In addition,the SVM is trained for the second time by adding hard samples to reduce the error detection rate.It is showed that the improved pedestrian detection and tracking method proposed in this paper achieves strong robustness and significantly detection performance.
出处
《科技视界》
2020年第15期34-36,共3页
Science & Technology Vision
基金
贺州学院校级科研项目“智能视频中人体的可靠检测与跟踪算法研究”研究成果(2017ZZZK06)
广西区级大学生创新训练计划项目(201811838185)。