Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-time Human Motion Analysis by Image Skeletonization
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Detecting Salient Motion by Accumulating Directionally-Consistent Flow
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
What Can Projections of Flow Fields Tell Us About the Visual Motion
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
An architecture for a self configurable video supervision
AREA '08 Proceedings of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams
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In this paper we address the context of visual surveillance in outdoor environments involving the detection of moving objects in the observed scene. In particular, a reliable foreground segmentation, based on a background subtraction approach, is explored. We firstly address the problem arising when small movements of background objects, as trees blowing in the wind, generate false alarms. We propose a background model that uses a supervised training for coping with these situations. In addition, in real outdoor scenes the continuous variations of lighting conditions determine unexpected intensity variations in the background model parameters. We propose a background updating algorithm that work on all the pixels in the background image, even if covered by a foreground object. The experiments have been performed on real image sequences acquired in a real archeological site.