C4.5: programs for machine learning
C4.5: programs for machine learning
Estimating attributes: analysis and extensions of RELIEF
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Machine Learning
Less is More: Active Learning with Support Vector Machines
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Detecting Moving Shadows: Algorithms and Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Moving Shadow and Object Detection in Traffic Scenes
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Detecting Objects, Shadows and Ghosts in Video Streams by Exploiting Color and Motion Information
ICIAP '01 Proceedings of the 11th International Conference on Image Analysis and Processing
Learning to Detect Moving Shadows in Dynamic Environments
IEEE Transactions on Pattern Analysis and Machine Intelligence
On line background modeling for moving object segmentation in dynamic scenes
Multimedia Tools and Applications
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In this paper, we tackle the shadow problem in depth for a better foreground segmentation. We propose a novel variant of co-training technique for shadow detection and removal in uncontrolled scenes. This variant works according to a powerful temporal behavior. Setting co-training parameters is based on an extensive experimental study. The proposed co-training variant runs periodically to obtain more generic classifier, thus improving speed and classification accuracy. An experimental study by quantitative, qualitative and comparative evaluations shows that the proposed method can detect shadow robustly and remove the ‘cast' part accurately from videos recorded by a static camera and under several constraints.