Tracking vehicles is an important and challenging issue in video-based intelligent transportation systems and has been broadly investigated in the past. This paper presents a robust and real-time method for tracking vehicles and the proposed algorithm includes two stages: vehicle detection, vehicle tracking. Vehicle detection is a key step and the concept of tracking vehicle is built upon the vehicle-segmentation method. According to the segmented vehicle shape, we propose a three-step prediction method based on the Kalman filter to track each vehicle. The proposed method has been tested on a number of monocular traffic-image sequences and the experimental results show that the algorithm is robust and real-time. The correct rate of vehicle tracking is higher than 85 percent, independent of environmental conditions.
Real-time vehicles tracking based on Kalman filter in a video-based ITS
2005
4 Seiten, 8 Quellen
Conference paper
English
3D pose estimation for articulated vehicles using Kalman-filter based tracking
British Library Online Contents | 2016
|Moving Vehicle Tracking Based on Kalman Filter
Trans Tech Publications | 2011
|A real-time alignment algorithm based on Kalman filter
IEEE | 2006
|Extended Kalman Filter Based Magnetic Guidance for Intelligent Vehicles
British Library Conference Proceedings | 2006
|