Passenger flow volume detection method and system based on computer vision

Abstract

The invention discloses a passenger flow statistics method based on a computer visual perception and system thereof. A video image collecting device can be placed at top end of an entrance or an exit of passages such as airport, subway, railway station, bus station, exhibition and so on to collect video images of passenger flows. A processor processes the video images collected by a computer visual perception algorithm to obtain a characteristic point of the image and to obtain a characteristic point trace by processing continuous image sequences within a period of time. Restricting the characteristic trace in time-space obtains smooth and continuous trace and clusters obtained characteristic traces to obtain number of passenger flows so as to obtain real time and accurate passenger flow information. The invention combines visual device and algorithm of computer to count number of the passenger flow accurately under a compact passenger flow circumstance. The obtained passenger flow information can be used as ground of safety monitor, operation management and line layout.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a computer vision-based passenger flow detection method and system. Background technique [0002] With the improvement of social security needs, closed-circuit television monitoring systems are generally installed in various public places, especially in airports, subways, railway stations, bus stations, exhibitions and other passenger-intensive places, the number of cameras is more intensive. In ordinary monitoring, it is usually only manual monitoring of the obtained monitoring content. Due to the large number of camera positions and the heavy workload of manual monitoring, most of the camera data can only play the role of recording, and cannot excavate the video. Abundant and large amount of useful information in the monitoring system. [0003] Due to the widespread use of video surveillance, computer vision-based pedestrian detection and tracking has become a very acti...

AI Technical Summary

Problems solved by technology

However, there are serious mutual occlusion problems in crowded places, so the traditional background difference method based on patch detection and tracking cannot solve the following problems:

[0004] 1. In the case of dense passenger flow, there is only limited background, and the background cannot even be extracted;

[0005] 2. When pedestrians are crowded, there is serious mutual occlusion among pedestrians, as well as occlusion of backpacks and other items;

[0006] 3. Video images with dense passenger flow often contain a large number of irregular movements, and the characteristic information of the target is limited. Generally, more than two frames of video images are required to detect a single moving target;

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