Bayesian Modeling of Dynamic Scenes for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Computing Surveys (CSUR)
Visual Monitoring-Based Railway Grade Crossing Surveillance System
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 2 - Volume 02
An adaptive, real-time, traffic monitoring system
Machine Vision and Applications
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In the paper we present an innovative computer vision based rail crossing protection system. A camera installed on top of a mast overlooking the crossing continuously monitors the scene, searching for objects that have stopped on the rail tracks. The system is designed to transmit images of the incident to the approaching trains as soon as any conflictive object has been detected. A simple user interface on board of the train displays the image sequence with a graphical aid clearly identifying the offending object in the image. In that way, train drivers are alerted of the presence of possible obstacles well before the train has approached the crossing. The system we describe operates autonomously for long periods of time without human intervention and adapts automatically to the changing environmental conditions. Several innovations, designed to deal with the above circumstances, are proposed in the paper, including: an adaptive segmentation algorithm, an innovative method for the detection of stopped objects and differentiated approaches for day and night processing.