A Method of Automatic Pedestrian Counting in Metro Station Based on Machine Vision
Chen Yan-ya · Journal of Highway and Transportation Research and Development · 2013
Now it is difficult to use the method of automatic counting pedestrians in metro station based on machine vision because of its low precision and poor stability.To solve this problem,we proposed a novel method of automatic counting pedestrians common in metro station.Our method achieved the function of pedestrian recognition suitable for short-shot and non-direct downward view for the general layout of cameras in metro stations.First,this method collects the Haar features from pedestrian head samples and detects the pedestrian head using strong classifier trained by AdaBoost algorithm.Second,considering different locations in image,this method removed the mistake detection which is too big or too small using bilinear interpolation algorithm according to the principle of put quality before quantity.Finally,according to the detections of pedestrian head,we designed the pedestrian tracking algorithm which includes pedestrian object clustering,break frame-sequence merging and pedestrian leaving.The experimental result shows that using our method in metro station to count people automatically is very effective.Its accuracy reached 90%,so it can be applied in practice.