Logic-Based Granular Prototyping
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Multi Feature Path Modeling for Video Surveillance
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A Multi-Object Tracking System for Surveillance Video Analysis
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Representation and Recognition of Events in Surveillance Video Using Petri Nets
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 7 - Volume 07
Detecting Motion Patterns via Direction Maps with Application to Surveillance
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Real-Time Video Surveillance with Self-Organizing Maps
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CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
An Architecture for Automated Scene Understanding
CAMP '05 Proceedings of the Seventh International Workshop on Computer Architecture for Machine Perception
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This article presents a surveillance system composed of video cameras. A localization is made using the information obtained from video cameras and the proper set of attributes is selected. An uncertainty measurement is performed based on the similarity with the nearest prototype and the dissimilarity from the rest of prototypes. The best granularity is also determined.