A smart camera based traffic enforcement system: experiences from the field
Oliver Sidla, Gernot Loibner · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
The observation and monitoring of traffic with smart vision systems for the purpose of improving traffic safety has a big potential. Embedded vision systems can count vehicles and estimate the state of traffic along the road, they can supplement or replace loop sensors with their limited local scope, radar which measures the speed, presence and number of vehicles. This work presents a vision system which has been built to detect and report traffic rule violations at unsecured railway crossings which pose a threat to drivers day and night. Our system is designed to detect and record vehicles passing over the railway crossing after the red light has been activated. Sparse optical flow in conjunction with motion clustering is used for real-time motion detection in order to capture these safety critical events. The cameras are activated by an electrical signal from the railway when the red light turns on. If they detect a vehicle moving over the stopping line, and it is well over this limit, an image sequence will be recorded and stored onboard for later evaluation. The system has been designed to be operational in all weather conditions, delivering human-readable license plate images even under the worst illumination conditions like direct incident sunlight direct view into or vehicle headlights. After several months of operation in the field we can report on the performance of the system, its hardware implementation as well as the implementation of algorithms which have proven to be usable in this real-world application.