Model-based object tracking in monocular image sequences of road traffic scenes
International Journal of Computer Vision
Digital video processing
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Markov random field modeling in image analysis
Markov random field modeling in image analysis
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
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IEEE Transactions on Intelligent Transportation Systems
Detection of moving cast shadows for object segmentation
IEEE Transactions on Multimedia
Detecting moving objects, ghosts, and shadows in video streams
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical modeling of complex backgrounds for foreground object detection
IEEE Transactions on Image Processing
Traffic Density Estimation with On-line SVM Classifier
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Adaptive shadow estimator for removing shadow of moving object
Computer Vision and Image Understanding
Perception-Based lighting adjustment of image sequences
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
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ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
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This paper presents an approach of moving vehicle detection and cast shadow removal for video based traffic monitoring. Based on conditional random field, spatial and temporal dependencies in traffic scenes are formulated under a probabilistic discriminative framework, where contextual constraints during the detection process can be adaptively adjusted in terms of data-dependent neighborhood interaction. Computationally efficient algorithm has been developed to discriminate moving cast shadows and handle nonstationary background processes for real-time vehicle detection in video streams. Experimental results show that the proposed approach effectively fuses contextual dependencies and robustly detects moving vehicles under heavy shadows even in grayscale video.