Subway station passenger flow statistics method based on face recognition

Abstract

The invention provides a subway station passenger flow statistics method based on face recognition, and belongs to the technical field of rail transit operation management. According to the method, astation control room processor analyzes images acquired by image acquisition devices mounted at entrances and exits of a station and entrances and exits of shielding doors, extracts face images, and performs functional processing such as face recognition, entrance and exit people counting, face tracking based on a hash algorithm, automatic capture and automatic storage; and the station control room terminal performs station passenger flow statistics and draws a passenger flow time distribution diagram. Real-time statistics of passenger flow in a station is achieved, and figure images are tracked to identify criminals; a passenger flow time distribution diagram is drawn in real time, and reference data are provided for subway operation managers to complete safety monitoring, reasonably arrange operation plans, drive dispatch, route planning design and the like. The method is high in recognition rate, strong in real-time performance and good in practicability, and can be used for passenger flow statistics of other places.

Description

technical field [0001] The invention relates to the technical field of rail transit operation management, in particular to a face recognition-based passenger flow statistics method in subway stations. Background technique [0002] Subway stations are important nodes in the urban rail transit network. Passenger flow congestion often occurs. When the large passenger flow approaches or exceeds the passenger flow carrying capacity of the station, passenger flow guidance will face severe challenges, and safety hazards such as stranded, crowded, and even trampled will occur. The size of the station passenger flow is directly related to passenger safety, operation safety and service quality. [0003] Existing passenger flow counting techniques in subway stations are mainly divided into the following types: (1) The traditional method of manually counting passenger flow on the platform, its main defect is: it cannot timely and accurately count the passenger flow in the station, which...

AI Technical Summary

Problems solved by technology

[0003] The existing counting techniques for passenger flow in subway stations are mainly divided into the following types: (1) The traditional method of manually counting passenger flow on the platform, its main defect is: it cannot timely and accurately count the passenger flow in the station, which requires a lot of human and financial resources

(2) AFC data analysis, that is, the use of automatic ticketing system statistics, its main defect is: mainly for the statistics of the passenger flow in and out of each gate, it is impossible to make statistics on the entrance and exit of screen doors or the number of train doors going up and down

(3) Video monitoring method, that is, image intelligent analysis technology, its main defects are: video analysis and processing workload is large, and there are requirements for wide field of view and high installation structure for application occasions

In all domestic stations, only cameras are equipped to monitor the station hall, platform and carriages, and there is no special video passenger flow statistics equipment

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