Pedestrian Detection and Tracking for Counting Applications in Metro Station

Abstract

A pedestrian counting method based on Haar-like detection and template-matching algorithm is presented. The aim of the method is to count pedestrians that are in a metro station automatically using video surveillance camera. The most challenging problem is to count pedestrians accurately in the case of not changing the position of the surveillance camera, because the view that surveillance camera uses in a metro station is always short-shot and nondirect downward view. In this view, traditional methods find it difficult to count pedestrians accurately. Hence, we propose this novel method. In addition, in order to improve counting accuracy more, we present a method to set the parameter value with a threshold-curve instead of a fixed threshold. The results of experiments show the high accuracy of our method.