Multi-modal and multi-camera attention in smart environments
Proceedings of the 2009 international conference on Multimodal interfaces
A Multi-modal Attention System for Smart Environments
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
Survey on contemporary remote surveillance systems for public safety
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Active vision in robotic systems: A survey of recent developments
International Journal of Robotics Research
Intelligent multi-camera video surveillance: A review
Pattern Recognition Letters
Online control of active camera networks for computer vision tasks
ACM Transactions on Sensor Networks (TOSN)
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In this paper, a novel reconfigurable surveillance system that incorporates multiple active-vision sensors is presented. The proposed system has been developed for visual-servoing and other similar applications, such as tracking and state estimation, which require accurate and reliable target surveillance data. In the specific implementation case discussed herein, the position and orientation of a single target are surveyed at predetermined time instants along its unknown trajectory. Dispatching is used to select an optimal subset of dynamic sensors, to be used in a data-fusion process, and maneuver them in response to the motion of the object. The goal is to provide information of increased quality for the task at hand, while ensuring adequate response to future object maneuvers. Our experimental system is composed of a static overhead camera to predict the object's gross motion and four mobile cameras to provide surveillance of a feature on the object (i.e., target). Object motion was simulated by placing it on an xy table and preprogramming a path that is unknown to the surveillance system. The selected cameras are independently and optimally positioned to estimate the target's pose (a circular marker in our case) at the desired time instant. The target data obtained from the cameras, together with their own position and bearing, are fed to a fusion algorithm, where the final assessment of the target's pose is determined. Experiments have shown that the use of dynamic sensors, together with a dispatching algorithm, tangibly improves the performance of a surveillance system