Monitoring systems of outdoor environments for surveillance applications need real time solutions for complex computer vision problems. However, advanced visual surveillance systems not only need to detect and track moving objects but also to interpret their pattern of behaviour. This work aims at presenting a method based on the use of neural networks for classification of moving tracked objects. Application scenario consists of an entrance access of a touristic village crossed by vehicles and the main aim of the method is to recognise possible presence of pedestrians in the zone.
A neural-network approach for moving objects recognition in color image sequences for surveillance applications
Carlo S Regazzoni
1999-01-01
Abstract
Monitoring systems of outdoor environments for surveillance applications need real time solutions for complex computer vision problems. However, advanced visual surveillance systems not only need to detect and track moving objects but also to interpret their pattern of behaviour. This work aims at presenting a method based on the use of neural networks for classification of moving tracked objects. Application scenario consists of an entrance access of a touristic village crossed by vehicles and the main aim of the method is to recognise possible presence of pedestrians in the zone.
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