izvorni znanstveni rad
Development of computing power and cheap video cameras enabled today’s traffic management systems to include more cameras and computer vision applications for transportation system monitoring and control. Combined with image processing algorithms cameras are used as sensors to measure road traffic parameters like flow, origindestination matrices, classify vehicles, etc. In this paper development of a system capable to measure traffic flow and estimate vehicle trajectories on multiple lanes using only one static camera is described. Vehicles are detected as moving objects using foreground and background image segmentation. Adjacent pixels in the moving objects image are grouped together and a weight factor based on cluster area, cluster overlapping area and distance between multiple clusters is computed to enable multiple moving object tracking. To ensure real time capabilities, image processing algorithm computation distribution between CPU and GPU is applied. Described system is tested using real traffic video footage obtained from Croatian highways.
Multiple object detection ; intelligent transportation system (ITS) ; vehicle detection ; vehicle tracking ; algorithm parallelization ; trajectory estimation
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