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Pattern Recognition Letters
Visual surveillance by dynamic visual attention method
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Real-time people localization and tracking through fixed stereo vision
Applied Intelligence
Robust vehicle and traffic information extraction for highway surveillance
EURASIP Journal on Applied Signal Processing
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Expert Systems with Applications: An International Journal
Knowledge-Based Road Traffic Monitoring
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Neural Information Processing
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Engineering Environment-Mediated Multi-Agent Systems
Vehicle Detection Based on Color and Edge Information
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Front-view vehicle detection by Markov chain Monte Carlo method
Pattern Recognition
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Multidimensional Systems and Signal Processing
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Pattern Recognition Letters
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Information Systems Frontiers
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IEEE Transactions on Intelligent Transportation Systems
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IEEE Transactions on Intelligent Transportation Systems
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CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 2
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Expert Systems with Applications: An International Journal
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ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
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IWICPAS'06 Proceedings of the 2006 Advances in Machine Vision, Image Processing, and Pattern Analysis international conference on Intelligent Computing in Pattern Analysis/Synthesis
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International Journal of Computational Vision and Robotics
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Multimedia Tools and Applications
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Machine Vision and Applications
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This paper presents algorithms for vision-based detection and classification of vehicles in monocular image sequences of traffic scenes recorded by a stationary camera. Processing is done at three levels: raw images, region level, and vehicle level. Vehicles are modeled as rectangular patches with certain dynamic behavior. The proposed method is based on the establishment of correspondences between regions and vehicles, as the vehicles move through the image sequence. Experimental results from highway scenes are provided which demonstrate the effectiveness of the method. We also briefly describe an interactive camera calibration tool that we have developed for recovering the camera parameters using features in the image selected by the user