Abstract: In the city intelligent video monitoring, it is necessary to track the moving object in real time. Aiming at the problems of the traditional moving object detection, for example, the target is easy to lose, low tracking rate and poor real-time performance, a moving object tracking detection method based on the improved optical flow characteristics is proposed to track the moving pedestrian object. Firstly, the improved Vibe moving background modeling method is used to detect the moving pedestrian in the video. Then the Shi-Tomasi corner detection and LK optical flow method are combined. The corner detection results are integrated into LK optical flow method, and the moving optical flow features of the detected corner points are extracted. Finally, Kalman filter is used to predict and track the pedestrians, and the Hungarian optimal matching algorithm is used to achieve continuous matching of moving objects and tracking of moving objects. The simulation results show that the proposed method can detect and track the moving objects in the video, and it has better recognition effect, and the detection efficiency is improved.

Key words: moving target tracking, background modeling, Shi-Tomasi corner detection, LK optical flow