Exploiting temporal statistics for events analysis and understanding

Authors:
Christian Micheloni;Lauro Snidaro;Gian Luca Foresti
Affiliations:
Department of Mathematics and Computer Science, Via delle Scienze 206, University of Udine, Via delle Scienze 206, 33100 Udine, UD, Italy;Department of Mathematics and Computer Science, Via delle Scienze 206, University of Udine, Via delle Scienze 206, 33100 Udine, UD, Italy;Department of Mathematics and Computer Science, Via delle Scienze 206, University of Udine, Via delle Scienze 206, 33100 Udine, UD, Italy
Venue:
Image and Vision Computing
Year:
2009

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Abstract

In this paper, we propose a technique for detecting anomalous events in outdoor areas monitored by a video surveillance system. In particular, the focus is on the time spent by an object to carry out simple events. To have a statistical representation of the time commonly required to perform certain activities, mixtures of Gaussians are maintained for each event type. Such statistics are then exploited both for the analysis of simple activities and for discovering anomalous situations, eventually alerting the operator. To this end, a novel way of visualizing results is also discussed. Experiments have been performed on a multi-camera system for parking lot security.