Detecting the location and identity of users is a first step in creating contextaware
applications for technologically-endowed environments. We propose a system that
makes use of motion detection, person tracking, face identification, feature-based identification,
audio-based localization, and audio-based identification modules, fusing information
with particle filters to obtain robust localization and identification. The data streams are
processed with the help of the generic client-server middleware SmartFlow, resulting in a
flexible architecture that runs across different platforms.
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