Abstract
Video-surveillance processing chains are complex software systems, exhibiting high degrees of variability along several dimensions. At the specification level, the number of possible applications and type of scenarios is large. On the software architecture side, the number of components, their variations due to possible choices among different algorithms, the number of tunable parameters... make the processing chain configuration rather challenging. In this paper we describe a framework for design, deployment, and run-time adaptation of video-surveillance systems—with a focus on the run time aspect. Starting from a high level specification of the application type, execution context, quality of service requirements... the framework derives valid possible system configurations through (semi) automatic model transformations. At run-time, the framework is also responsible for adapting the running configuration to context changes. The proposed framework relies on Model-Driven Engineering (MDE) methods, a recent line of research in Software Engineering that promotes the use of software models and model transformations to establish a seamless path from software specifications to system implementations. It uses Feature Diagrams which offer a convenient way of representing the variability of a software system. The paper illustrates the approach on a simple but realistic use case scenario of run time adaptation.
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Moisan, S., Rigault, JP., Acher, M., Collet, P., Lahire, P. (2011). Run Time Adaptation of Video-Surveillance Systems: A Software Modeling Approach. In: Crowley, J.L., Draper, B.A., Thonnat, M. (eds) Computer Vision Systems. ICVS 2011. Lecture Notes in Computer Science, vol 6962. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23968-7_21
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DOI: https://doi.org/10.1007/978-3-642-23968-7_21
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