Multimodal identification and localization of users in a smart environment

Abstract

Detecting the location and identity of users is a first step in creating context-aware 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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Correspondence to Albert Ali Salah.

Additional information

This work is supported by Spanish projects SAPIRE (TEC2007-65470) and PROVEC (TEC2007-66858/TCM) and Dutch projects BRICKS/BSIK and BASIS IOP GenCom.

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Salah, A.A., Morros, R., Luque, J. et al. Multimodal identification and localization of users in a smart environment. J Multimodal User Interfaces 2, 75–91 (2008). https://doi.org/10.1007/s12193-008-0008-y

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Keywords

  • Multimodal tracking
  • Multimodal identification
  • Particle filters
  • Smart rooms