Leveraging e-transportation in real-time traffic evacuation management
Electronic Commerce Research and Applications
Applications of moving windows technique to autonomous vehicle navigation
Image and Vision Computing
A double layer background model to detect unusual events
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
A new approach for vehicle detection in congested traffic scenes based on strong shadow segmentation
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Clustering of vehicle trajectories
IEEE Transactions on Intelligent Transportation Systems
Traffic incident classification at intersections based on image sequences by HMM/SVM classifiers
Multimedia Tools and Applications
Behavior pattern extraction by trajectory analysis
Frontiers of Computer Science in China
Biologically-inspired multi-object tracking algorithm applied to traffic monitoring
CIMMACS'05 Proceedings of the 4th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics
Integrated video object tracking with applications in trajectory-based event detection
Journal of Visual Communication and Image Representation
Advanced formation and delivery of traffic information in intelligent transportation systems
Expert Systems with Applications: An International Journal
Journal of Signal Processing Systems
Traffic event classification at intersections based on the severity of abnormality
Machine Vision and Applications
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The goal of this project is to monitor activities at traffic intersections for detecting/predicting situations that may lead to accidents. Some of the key elements for robust intersection monitoring are camera calibration, motion tracking, incident detection, etc. In this paper, we consider the motion-tracking problem. A multilevel tracking approach using Kalman filter is presented for tracking vehicles and pedestrians at intersections. The approach combines low-level image-based blob tracking with high-level Kalman filtering for position and shape estimation. An intermediate occlusion-reasoning module serves the purpose of detecting occlusions and filtering relevant measurements. Motion segmentation is performed by using a mixture of Gaussian models which helps us achieve fairly reliable tracking in a variety of complex outdoor scenes. A visualization module is also presented. This module is very useful for visualizing the results of the tracker and serves as a platform for the incident detection module.