基于光流法和行人面积特征的人数统计方法研究

为了提高视频监控领域中出入口的人数统计的准确率，提出构建一种近似 俯视运动行人面积作为人数统计的特征。使用垂直悬挂的单目摄像头对出入口进行拍摄，设 置一条虚拟计数线，利用Lucas-Kanade 光流算法计算计数线上像素的速度矢量，并构建近 似俯视运动行人面积作为特征对过线人数进行估计并计数。实验结果表明，使用该方法可以 降低光照原因产生的阴影以及图像预处理对人数统计的干扰，比较准确地对出入口进行人数 统计。

A method for people counting based on optical flow and pedestrian size

In order to improve the accuracy of people counting in video surveillance, an approximate pedestrian size in the vertical view is proposed as a feature when the camera is mounted vertically. In this method, a virtual detection line is set up and the Lucas-Kanade optical flow algorithm is used to calculate the velocity vector of pixels on the line. The method constructs the approximate pedestrian size in the vertical view to estimate the number of people passing through the detection line. Experimental results show that this method can reduce interference caused by shadows and image preprocessing, and can accurately count the number of people passing through the entrance.