Abstract
How to automatically monitor wide critical open areas is a challenge to be addressed. Recent computer vision algorithms can be exploited to avoid the deployment of a large amount of expensive sensors. In this work, we propose our object tracking system which, combined with our recently developed anomaly detection system. can provide intelligence and protection for critical areas. In this work. we report two case studies: an international pier and a city parking lot. We acquire sequences to evaluate the effectiveness of the approach in challenging conditions. We report quantitative results for object counting, detection, parking analysis, and anomaly detection. Moreover, we report state-of-the-art results for statistical anomaly detection on a public dataset.
Highlights
Introduction and Related WorkThe monitoring of infrastructures is a compelling need both for buildings and open areas
Many areas need constant surveillance to ensure the enforcement of rules and laws, and the decreasing cost of sensors has supported the fast deployment of network cameras
Regarding the spatial counting task, we annotated the positions of people, cars, trucks. and motorbikes which werein the scene
Summary
The monitoring of infrastructures is a compelling need both for buildings and open areas. With a special use case of smart buildings [1], is facilitated by the possibility of deploying and fusing multiple sensors. Wide areas may be present in buildings too, as in the case of airports or malls. The use of wide area monitoring systems with network cameras has recently increased due to the recent request for more security [2]. Many areas need constant surveillance to ensure the enforcement of rules and laws, and the decreasing cost of sensors has supported the fast deployment of network cameras. When dealing with wide areas, the use of manned surveillance, even with the use of a camera network, is extremely challenging
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