With the acceleration of urbanization process in recent years, urban rail transit construction has expanded rapidly and the burden of the traffic network operators increase year by year. The networked operation has become the inevitable trend of developmenting urban rail transit, but meanwhile networked operation has a new and higher requirement for information sharing and system security. The real-time passenger state detection and early warning system this paper involved come from a subtopic named "urban rail transport network operational security and key technology study" which is from National Science and Technology Supported Program, that is, through acquiring, accessing and integrating the data from road network infrastructure, operating vehicle state, transport organizations scheme and passenger distribution to ultimately build the Urban Rail Network Operation Data Center.The prime task of this paper is based on digital image processing and machine learning theory, to sum up the passenger flow within the monitored area. Ultimately, to build Passenger Flow Detection Subsystem. Targets detecting, which is the main work of this paper, centered on designing and implementing of two modules, machine learning and video analysis. The machine learning module completed HOG Feature Extraction and Training SVM classifier; Video analysis module first discusses a fast algorithm of HOG feature extraction, to improve the speed of the target detection. Then use the pyramid multi-resolution method to detect different sizes target within the detection area. Finally, introduce the multi-target fusion method and the detailed flow to realize. All the tasks mentioned above are completed by myself.The system is in beta and perfect stage has not yet formally launched. Testing has shown that the system’s detection rate has reached more than95%in normal light. When the light is significantly reduced and enhanced, will lead to the detection rate decreased to varying degrees. The Passenger status real-time detection and early warning system provide the passenger flow distribution data of each detection point for urban rail operations management, and provide strong technical support for its development of effective security operations management, emergency rescue and joint coordination scheme. |