Vision-based object detection for passenger’s safety in railway platform

In this paper, we propose a vision-based object detection algorithm for railway passenger’s safety. The proposed algorithm uses three-dimensional position information with stereo cameras for minimizing various illuminant effects in railway platform environment, such as ambient illumination changes due to train arrival/departure in the scene. The detection process analyzes scene and detects both four different train status and fallen objects in preset monitoring area. To solve the detection problem in conventional two-dimensional detection system, the system detects object in three dimensionally by using stereo vision algorithm. We verify the system performance with extensive experimental results in a metro station. We expect the proposed algorithm will play a key role in establishing highly intelligent monitoring system for passenger’s safety for future railway environment.