Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Visual Method for Assessing the Relative Performance of Edge-Detection Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance characterisation in computer vision: statistics in testing and design
Imaging and vision systems
Using Adaptive Tracking to Classify and Monitor Activities in a Site
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A Real-Time System for Monitoring of Cyclists and Pedestrians
VS '99 Proceedings of the Second IEEE Workshop on Visual Surveillance
Video Surveillance of Interactions
VS '99 Proceedings of the Second IEEE Workshop on Visual Surveillance
Frame-Rate Omnidirectional Surveillance & Tracking of Camouflaged and Occluded Targets
VS '99 Proceedings of the Second IEEE Workshop on Visual Surveillance
View-Based Detection and Analysis of Periodic Motion
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
State of the art on automatic road extraction for GIS update: a novel classification
Pattern Recognition Letters
Efficient adaptive density estimation per image pixel for the task of background subtraction
Pattern Recognition Letters
Efficient hierarchical method for background subtraction
Pattern Recognition
A Real-time Vision-based Vehicle Tracking and Traffic Surveillance
SNPD '07 Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01
Intelligent Vehicle Counting Method Based on Blob Analysis in Traffic Surveillance
ICICIC '07 Proceedings of the Second International Conference on Innovative Computing, Informatio and Control
AREA '08 Proceedings of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams
Using self-organising maps in the detection and recognition of road signs
Image and Vision Computing
Coupled multi-object tracking and labeling for vehicle trajectory estimation and matching
Multimedia Tools and Applications
Detection and classification of vehicles
IEEE Transactions on Intelligent Transportation Systems
Automatic traffic surveillance system for vehicle tracking and classification
IEEE Transactions on Intelligent Transportation Systems
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In this paper we propose a new dynamic algorithm able to automatically identify the background from images under severe changes of the environmental conditions. The algorithm exploits motion estimation techniques and background subtraction methods. The proposed scheme is implemented in road construction application scenarios under outdoor environments in which the camera vision is dramatically varied with respect to the weather conditions. Despite such variations, the background can be automatically detected improving the tracking performance for the vehicles and just assisting survey engineers in defining possible errors in the design yielding as deviations between the actual and the ideal trajectory of the vehicle over a turn. Experimental results in real-life road surveillance systems reveal the efficiency of the proposed scheme regardless of significant background changes. In addition, the proposed algorithm requires low computational complexity.