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Integration of computer vision and RTL technologies for ambient intelligence and Human-Computer Interaction Massimiliano Dibitonto  DRIEI Dottorato di Ricerca in Ingegneria Elettronica e Informatica University of Cagliari, Italy
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Wireless Real Time Locating Systems ,[object Object],[object Object],[object Object],[object Object],[object Object]
Wireless Real Time Locating Systems ,[object Object],[object Object],[object Object],UWB ACTIVE RFID  1cm 1cm 10 cm 1 m 10 m Outdoor Semi urban Urban Building Room Objects GPS  Wi-Fi Passive RFID  accuracy ZigBee
Computer Vision ,[object Object],[object Object],[object Object],[object Object]
CV and RTLS “complementarity” ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Both systems try to aswer to two  MAIN  common questions:  Who/What  and  Where The main differences are
CV and RTLS “complementarity” ,[object Object],RTLS CV 2d – 3d position temperature, humidity, pressure, acceleration, etc.. unique  ID Orientation, gestures , biometrics, fine grained movements, recognition of different features Other sensors  onboard: Fusion models can be developed to harvest the information gained from the two systems
CV and RTL/RFID fusion ,[object Object],[object Object],[object Object],[object Object]
CV and RTL/RFID fusion: objects/people recognition ,[object Object],[object Object],*Cerrada, C.; Salamanca, S.; Perez, E.; Cerrada, J.A.; Abad, I., "Fusion of 3D Vision Techniques and RFID Technology for Object Recognition in Complex Scenes,"  Intelligent Signal Processing, 2007. WISP 2007. IEEE International Symposium on  , vol., no., pp.1-6, 3-5 Oct. 2007
CV and RTL fusion: Localization ,[object Object],[object Object],[object Object],[object Object],CV RTLS ,[object Object]
CV and RTL/RFID fusion:  Behaviour analysis ,[object Object],[object Object],* Krahnstoever, N.; Rittscher, J.; Tu, P.; Chean, K.; Tomlinson, T., "Activity Recognition using Visual Tracking and RFID,"  Application of Computer Vision, 2005. WACV/MOTIONS '05 Volume 1. Seventh IEEE Workshops on  , vol.1, no., pp.494-500, 5-7 Jan. 2005 Frame Grabber Articulated Tracker RFID Reader Custom Pose Estimation Circuitery Activity recognition
Objectives Outline Our research will point  to:
Objectives: integration models ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Proposed integration models Sequential model :  the RTL system act as a guide fro the vision based tracking system. The main benefit  is a reduction of the computational complexity but on the other hand it doesn’t detect people/object not equipped with a tag.
Proposed integration models Parallel model :  the  two systems works indipendently , then a data fusion system analyze the two outputs . Localization via RTL/RFID system Image analysis – object/person tracking  Comparison  of the obtained data
Proposed integration models ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Objectives: performance evaluation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Objectives: new HCI paradigms ,[object Object],[object Object],[object Object],[object Object],Interface adaptation module Multi agent system Context capture system RTLS Wireless Sensors and Actuators Network Computer Vision System
Objectives: usability evaluation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Possible Scenarios – Ambient Intelligence ,[object Object],[object Object],0100011100101000....
PhD Thesis Starting Point: A prototype of CV and RTL fusion at DIEE ,[object Object],[object Object],RTL and RFID services Video module Segnalation module
PhD Thesis Starting Point: A prototype of CV and RTL fusion at DIEE ,[object Object],[object Object]
Progress beyond SoA ,[object Object],[object Object],[object Object],[object Object],[object Object]
Put together different “worlds”..... ... toward new intelligent scenarios
[object Object],Department of Electrical and Electronic Engineering (PRA group) of University of Cagliari with its strong competence on Computer Vision Cattid fron Sapienza University for his competence on Human Computer Interaction and Real Time Locating Systems
[object Object],[object Object]

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Phd Thesis Project

  • 1. Integration of computer vision and RTL technologies for ambient intelligence and Human-Computer Interaction Massimiliano Dibitonto DRIEI Dottorato di Ricerca in Ingegneria Elettronica e Informatica University of Cagliari, Italy
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12. Objectives Outline Our research will point to:
  • 13.
  • 14. Proposed integration models Sequential model : the RTL system act as a guide fro the vision based tracking system. The main benefit is a reduction of the computational complexity but on the other hand it doesn’t detect people/object not equipped with a tag.
  • 15. Proposed integration models Parallel model : the two systems works indipendently , then a data fusion system analyze the two outputs . Localization via RTL/RFID system Image analysis – object/person tracking Comparison of the obtained data
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 23.
  • 24. Put together different “worlds”..... ... toward new intelligent scenarios
  • 25.
  • 26.

Editor's Notes

  1. Cooperative and non cooperative
  2. We are moving toward an Internet of Things scenario where objects and spaces are becoming “ intelligent ” and rich of information . This scenario is rising new challenges and new opportunities especially in the field of Human Computer Interaction . HCI paradigms are evolving toward “fluid” interfaces that become part of the surrounding environment and that are able to react to human behaviours and that should provide a natural interaction while interacting with complex systems, and avoid cognitive overload while accessing information and services Fusion of this different systems can be used to rethink the human-machine interactive experience developing new kind of interfaces. Integration models can be designed to use this systems as input device itself (i.e. proximity, gesture recognition) or use their outputs in more complex context capture systems and in multi agent systems to realize ambient that are “intelligent” allowing new kind of interaction paradigms between humans and machines.
  3. As traditional approaches of usability testing are suitable for testing individual applications or devices in an isolated manner there is the need to design new evaluation methodologies for this new kind of interfaces.