Abstract:
In this study, a vision based real-time traffic flow monitoring system has been developed to extract statistics passes through the intersections. A novel object tracking and data association algorithms have been developed using the bounding-box properties to estimate the vehicle trajectories. Then, rich traffic flow information such as directional and total counting, instantaneous and average speed of vehicles are calculated from the predicted trajectories. During the study, various parameters that affect the accuracy of vision based systems are examined such as camera locations and angles that may cause occlusion or illusion problems. In the last part, sample video streams are processed using both Kalman filter and new centroid-based algorithm for comparative study. The results show that the new algorithm performs 9.18% better than Kalman filter approach in general.
Description:
Bu yayın 06.11.1981 tarihli ve 17506 sayılı Resmî Gazete’de yayımlanan 2547 sayılı Yükseköğretim Kanunu’nun 4/c, 12/c, 42/c ve 42/d maddelerine dayalı 12/12/2019 tarih, 543 sayılı ve 05 numaralı Üniversite Senato Kararı ile hazırlanan Sakarya Üniversitesi Açık Bilim ve Açık Akademik Arşiv Yönergesi gereğince açık akademik arşiv sistemine açık erişim olarak yüklenmiştir.
