Image Analysis Using Mathematical Morphology
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spatiotemporal Segmentation Based on Region Merging
IEEE Transactions on Pattern Analysis and Machine Intelligence
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
A Noise Robust Method for Segmentation of Moving Objects in Video Sequences
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 4 - Volume 4
Detecting Moving Shadows: Algorithms and Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
IEEE Transactions on Circuits and Systems for Video Technology
Moving target detection and labeling in video sequence based on spatial-temporal information fusion
LSMS'07 Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications
A review of vision-based systems for soccer video analysis
Pattern Recognition
A multiple camera methodology for automatic localization and tracking of futsal players
Pattern Recognition Letters
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In this work, we consider the problem of background pixels information recovering which can be used, for example, in applications concerning segmentation and tracking of components in video images. Shortly, to recover the background of image sequences representing outdoor scenes, we consider a non-parametric morphological leveling operation, which takes into account the specific problem of lighting changes and the fact that we can have both slow and fast motion in the scene. We illustrate the segmentation of players based on the difference between image sequences and the corresponding recovered background representation. We also discuss the reduction of shadows in digital video of soccer games and show the good results of the whole background recovering and segmentation process.