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Sensor-based Situated, Individualized, and Personalized Interaction in Smart Environments

Sensor-based Situated, Individualized, and Personalized Interaction in Smart Environments. Sensor-based Situated, Individualized, and Personalized Interaction in Smart Environments. Simone Hämmerle, Matthias Wimmer , Bernd Radig, Michael Beetz Technische Universität München – Informatik IX.

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Sensor-based Situated, Individualized, and Personalized Interaction in Smart Environments

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  1. Sensor-based Situated, Individualized, and Personalized Interaction in Smart Environments Sensor-based Situated, Individualized, and Personalized Interaction in Smart Environments Simone Hämmerle, Matthias Wimmer, Bernd Radig, Michael Beetz Technische Universität München – Informatik IX

  2. SIP via sensors • Situation detection: • information about persons: name, location, focus of attention, posture, motion,… • Individualized settings: • desktop, avatar, input settings (gestures, voice commands,…) • Personalized settings: • user’s role, right management,… • SIP detection using sensors • more comprehensive SIP information • more intuitive HCI who when where what

  3. Our Test Bed Sensors: cameras, microphones, laser-range-sensors Actuators: monitor, speaker, video-wall Scenarios: • person localization • automatic login • meeting reminder • individualized gesture interaction

  4. Video

  5. person detection OpenCV (Haar-Face-Detector) person recognition OpenCV (Hidden Markov Models) person tracking developed at TUM laser-scanner based multiple hypothesis tracking,… gesture recognition developed at TUM motion templates, multiple classifiers,… mimic recognition developed at TUM point distribution model, optical flow,… Techniques (Computer Vision)

  6. Techniques (others) • natural language input • Java Sphinx 4 (origin CMU, now open source) • phonemes are already trained • we defined the words ( = concatenation of phonemes) • we defined the grammar ( = allowed sentences) • natural language output • provides the user with audio information • user can be mobile • FreeTTS 1.2 (sourceforge)

  7. Software architecture multi agent framework Dispatcher

  8. Conclusion • Advantages using sensors • additional and more exact context knowledge • unobtrusive system • Multi agent framework • distributed and scalable system • simply extensible to further scenarios • Overall semantic • semantic agent communication • central aggregation of semantic context knowledge • Leads to • more comprehensive SIP information • seamless integration of SIP information • intuitive HCI

  9. Thank you!

  10. Setup & Benefit • sensors for detection of SIP context: • cameras • microphones • laser-range-sensors • pressure-sensors, … • sensors provide knowledge about the SIP context • situation dependant services • intuitive HCI (human computer interface) • application scenarios: • support in meetings and presentations • intelligent House • external robot control

  11. Our Test Bed Sensors: Cameras, Microphones, Laser-Range-Sensors Actuators: Monitor, Speaker, Video-Wall Scenarios: • automatic login • meeting reminder • individualized gesture interaction • intuitive robot control • person localization

  12. person recognition (Bild) gesture recognition (Bild) Sensors

  13. Knowledgebase • Web Ontology Language (W3C)

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