Distributed Modular Toolbox for Multi-modal Context Recognition
David Bannach, Kai S. Kunze, Paul Lukowicz, Oliver Amft · 2006
Abstract. We present a GUI-based C++ toolbox that allows for build-ing distributed, multi-modal context recognition systems by plugging to-gether 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 tool-box we focus on here are a set of parameterizable algorithms including different filters, feature computations and classifiers, a runtime environ-ment 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 com-putation 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. 1