基于改进tld的监控视频车辆检测跟踪方法

Monitoring video vehicle detection tracking method based on improved TLD

Abstract

本发明公开了一种准确性高的、鲁棒性好的基于改进TLD的监控视频车辆检测跟踪算法,该算法采用基于车辆颜色特征的分块Cam Shift跟踪器替代L‑K光流的点跟踪器,通过Cam Shift所获取的车辆区域颜色直方图实现对跟踪目标的描述,再通过捕捉区域的颜色直方图相似性度量实现对跟踪目标在前后两帧间运动量的预估;进一步结合随机森林检测器获得车辆目标的粗略位置,以及通过P‑N学习实时地对检测器进行观测和对跟踪器进行定位,从而实现有效的车辆检测跟踪。
The invention discloses a monitoring video vehicle detection tracking method based on an improved TLD, which is high in accuracy and good in robustness. The monitoring video vehicle detection tracking method comprises steps of adopting a sub-block Cam Shift tracer based on vehicle color characteristics to replace an L-K light flow point tracer, realizing description of a tracked object through a vehicle area color histogram obtained by the Cam Shift, realizing activity amount estimation on the tracking object moving between a prior frame and a later frame through measuring the similarity of the color histograms in the capture area, further combining with a random forest detector to obtain a rough position of a vehicle object, and observing a detector and positioning the tracker in real time through P-N study so as to realize effective vehicle detection tracking.

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