Understanding metro station usage using Closed Circuit TeleVision cameras analysis

Abstract

Abstract-In this paper, we propose to show how video data available in standard CCTV transportation systems can represent a useful source of information for transportation infrastructure management, optimization and planning if adequately analyzed (e.g. to facilitate equipment usage understanding, to ease diagnostic and planning for system managers). More precisely, we present two algorithms allowing to estimate the number of people in a camera view and to measure the platform time-occupancy by trains. A statistical analysis of the results of each algorithm provide interesting insights regarding station usage. It is also shown that combining information from the algorithms in different views provide a finer understanding of the station usage. An end-user point of view confirms the interest of the proposed analysis.

Fast human detection from joint appearance and foreground feature subset covariances

“…We trained three new detectors relying on 2, 3 and 4-subset features (Fg-Cov-Avg-2 to Fg-CovAvg-4, respectively), and a combined detector based on 2, 3 and 4-subset features for the cascade levels 1 to 15, 16 to 25, and 26 to 30, respectively (Fg-Cov-Avg- [2,3,4]). Fig.…”

“…We expect the former to be more informative in the context of video surveillance than the latter ones. 2 When examining the features in H , we can qualitatively expect the intensity features to provide shape and texture information. The foreground features will mainly provide shape information, but not only thanks to the use of foreground probability maps as observations (e.g.…”

“…On the other hand, human detection can also be used on its own, without being involved in a more evolved framework like tracking. For instance, in [2], a human detector was continuously applied to count the number of people in different places of a metro station in order to provide usage statistics to metro operators or to detect abnormal situations (i.e. counts which differ from standard values observed at a given time and a given day of the week).…”

3D Vision-based Security Monitoring for Railroad Stations

“…These systems are focused on measuring the level of crowding on the passenger platforms of train services. If overcrowding is detected, the system will notify the station operators to take appropriate actions to prevent dangerous situations such as people falling off or being pushed onto the tracks [9][10][11][12][13][14]. Background subtraction is commonly used to locate passengers and thereby to estimate the crowd density [1][2][3][4][5]7] Edge information may be used to measure the regions occupied by passengers [1,4].…”

“…[5,6,8]. To detect abrupt and dangerous situations, object tracking has been implemented using a combined method of background subtraction, edge detection and motion detection [9][10][11][12][13][14]. An infrared camera was found to be useful to locate passengers [10].…”