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Color-Based Object Recognition by a Grid-Connected Robot Dog


Overview of the Demonstration:

This demonstration shows object recognition performed by a Sony Aibo robot dog. The dog is connected to a wide-area Grid system, potentially consisting of hundreds of computers located at several institutes in Europe, the United States, and Australia. Apart from the quality of recognition, we demonstrate the effectiveness of Grid usage in multimedia computing. Moreover, we show the ease with which multimedia applications can be integrated with Grid computing.


What we have to offer:

  Short movie showing our Aibo robot dog walking around, and recognizing the objects it has learned.
     
 
Promotional video "Color-Based Object Recognition by a Grid-Connected Robot Dog", which has won a most visionary research award at AAAI-07, and gained an "honourable mention" at the annual Dutch meeting between science and press: Bessensap 2007. see also the "Noorderlicht" pages of the Dutch broadcasting cooperation VPRO.
     
  Full image showing our World-Wide Aibo-Grid initialization GUI, which allows us to select computing resources worldwide with only a few mouse-clicks.
     
  Short movie showing the Aibo Object Recognition GUI, in which the 'learning' phase is performed for one object, while being connected to four cluster computers in Europe and one in Australia.
     
  Short movie showing about 50 out of 1,000 objects that our Aibo robot dog has learned.
     
  Pictures taken during demonstration sessions at international conferences and national ICT meetings.

     
  Picture shot during the making of the promotional video "Color-Based Object Recognition by a Grid-Connected Robot Dog", Amsterdam, The Netherlands, April 18, 2006.

     
  Poster used for our demonstration at ICME 2005, Amsterdam, The Netherlands, July 6-8, 2005.

     
  Poster used for our demonstrations at ECCV 2006 (Graz, Austria, May 7-13, 2006) and Supercomputing 2007 (Reno, NV, USA, November 10-16, 2007) - with a significant increase in the available resources since ICME 2005.



People:


Acknowledgements:

We would like to thank the following people for their support, and for granting us access to their cluster systems:

- Australia
  • Prof. David Abramson, Colin Enticott, Pim Amponpun (Monash University, Melbourne)
  • Prof. Lindsay Botten, Achim Casties, Vladas Leonas (Australian Centre for Advanced Computing and Communications, Sydney-Eveleigh)
  • Prof. Albert Zomaya, Philip McCrea, Chen Wang (University of Sydney)
  • Tony Adriaansen (CSIRO, Sydney)
- United States
  • Bhiksha Raj, Ron Johnson (Mitsubishi Electric Research Laboratories, Boston - Cambridge, MA)
  • Jason Leigh, Lance Long, Alan Verlo (University of Illinois at Chicago, IL)
  • Philip Papadopoulos (San Diego Supercomputer Center, University of California, San Diego, CA)
- Europe
  • Andreas Uhl, Ernst Forsthofer (Salzburg University, Salzburg, Austria)
  • Tobias Klug, Carsten Trinitis (Technical University Munich, Germany)
  • Daniele D'Agostino, Antonella Galizia (University of Genoa, Italy)
  • Marian Bubak, Patryk Lason, Lukasz Skital (University of Science and Technology, Krakow, Poland)
  • Norbert Meyer, Piotr Siwczak, Marek Zawadzki (Poznan Supercomputing & Networking Center, Poznan, Poland)
  • Jesus Marco de Lucas, Rafael Marco de Lucas (Instituto de Fisica de Cantabria, Santander, Spain)
  • Prof. Andrew Zisserman (Oxford University, United Kingdom)
- The Netherlands
  • Prof. Henri Bal, Thilo Kielmann, Andre Merzky, Kees Verstoep (Vrije Universiteit, Amsterdam)
  • Prof. Cees de Laat (Universiteit van Amsterdam)
We are grateful to Michiel van Liempt (Universiteit van Amsterdam) for his excellent efforts in implementing the original sequential object recognition code.
Finally, thanks go out to Edwin Steffens and Arnoud Visser for providing us with a Sony Aibo robot dog.

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