Abstract
We present a GUI-based C++ toolbox that allows for building distributed, multi-modal context recognition systems by plugging together reusable, parameterizable components. The goals of the toolbox are to simplify the steps from prototypes to online implementations on low-power mobile devices, facilitate portability between platforms and foster easy adaptation and extensibility. The main features of the toolbox we focus on here are a set of parameterizable algorithms including different filters, feature computations and classifiers, a runtime environment that supports complex synchronous and asynchronous data flows, encapsulation of hardware-specific aspects including sensors and data types (e.g., int vs. float), and the ability to outsource parts of the computation to remote devices. In addition, components are provided for group-wise, event-based sensor synchronization and data labeling. We describe the architecture of the toolbox and illustrate its functionality on two case studies that are part of the downloadable distribution.
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© 2006 Springer-Verlag Berlin Heidelberg
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Bannach, D., Kunze, K., Lukowicz, P., Amft, O. (2006). Distributed Modular Toolbox for Multi-modal Context Recognition. In: Grass, W., Sick, B., Waldschmidt, K. (eds) Architecture of Computing Systems - ARCS 2006. ARCS 2006. Lecture Notes in Computer Science, vol 3894. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11682127_8
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DOI: https://doi.org/10.1007/11682127_8
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