Abstract
Vision systems are camera networks, which perform computer vision using multiple cameras. Due to the directional characteristic of the image sensor, it is not feasible to observe large surveillance areas using stationary cameras. This drawback can be overcome by using active vision (AcVi) systems consisting of mobile cameras (called AcVi nodes), which are reconfigurable in both position and orientation. In case of a dynamic environment with moving targets, AcVi nodes can be repositioned during runtime in order to fulfill the overall observation objectives.
This paper is devoted to develop a generalized system architecture for AcVi systems in multi-target environments. Based on this architecture, we present a coordination mechanism making way for self-organization - a major paradigm of Organic Computing - in such systems. Our algorithm enables AcVi nodes to observe an area under surveillance by using their mobility. In contrast to stationary vision systems, only a fraction of the amount of nodes is needed to achieve the same observation quality. The algorithm has been evaluated by simulation with up to 10 nodes as used for example for surveillance scenarios. Results show that our coordination algorithm is able to cope with large numbers of nodes and targets and is robust towards real world disturbances like communication failure.
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Wittke, M., Grenz, C., Hähner, J. (2011). Towards Organic Active Vision Systems for Visual Surveillance. In: Berekovic, M., Fornaciari, W., Brinkschulte, U., Silvano, C. (eds) Architecture of Computing Systems - ARCS 2011. ARCS 2011. Lecture Notes in Computer Science, vol 6566. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19137-4_17
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DOI: https://doi.org/10.1007/978-3-642-19137-4_17
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