Crowd Monitoring for Underground Railway Station Based on Weighted Area Perspective Transformation

Crowd counting in dense crowd scene has become an important and difficult topic in the field of automatic surveillance system.Since there are some requirements in the orbital traffic,a crowd counting approach for underground railway station is proposed.A weighted area computing approach is presented according to the information of camera firstly.Then the crowd density is estimated using AdaBoost classifier with the difference of gradient orientation between head and body of people.The people number is counted according to the crowd density and the weighted area.The experiment results show that the proposed approach is effective and feasible for crowd counting in underground railway station.