Advertisement

Drawings as Input for Handheld Game Computers

  • Mannes Poel
  • Job Zwiers
  • Anton Nijholt
  • Rudy de Jong
  • Edward Krooman
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3814)

Abstract

The Nintendo DSTM is a hand held game computer that includes a small sketch pad as one of it input modalities. We discuss the possibilities for recognition of simple line drawing on this device, with focus of attention on robustness and real-time behavior. The results of our experiments show that with devices that are now becoming available in the consumer market, effective image recognition is possible, provided a clear application domain is selected. In our case, this domain was the usage of simple images as input modality for computer games that are typical for small hand held devices.

Keywords

Decision Tree Template Match Input Modality Image Recognition Interactive Game 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Douglas, D., Peucker, T.: Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. Canadian Cartographer 10, 112–122 (1973)Google Scholar
  2. 2.
    Anzai, Y.: Pattern Recognition and Machine Learning. Academic Press, London (1989)Google Scholar
  3. 3.
    Theodoridis, S., Koutroumbas, K.: Pattern Recognition. Academic Press, London (1999)Google Scholar
  4. 4.
    Pandya, A., Macy, R.: Pattern Recognition with Neural Networks in C++. CRC Press, Boca Raton (1996)Google Scholar
  5. 5.
    Fonseca, M., Pimentel, C., Jorge, J.: Cali: an online scribble recognizer for calligraphic interfaces. In: Proc. AAAI Spring Symposium on Sketch Understanding, pp. 51–58 (2002)Google Scholar
  6. 6.
    Caetano, A., Goulart, N., Fonseca, M., Jorge, J.: JavaSketchIT: Issues in sketching the look of user interfaces. In: Proc. AAAI Spring Symposium on Sketch Understanding, pp. 9–14 (2002)Google Scholar
  7. 7.
    Parizeau, M., Lemieux, A., Gagné, A.: Character recognition experiments using unipen data. In: Proc. Int. Conference on Document Analysis and Recognition, pp. 481–485 (2001)Google Scholar
  8. 8.
    Duda, R., Hart, P., Stork, D.: Pattern Classification. Wiley, New York (2001)MATHGoogle Scholar
  9. 9.
    Quinlan, R.: C4.5: programs for machine learning. Morgan Kaufmann Publishers Inc, San Francisco (1993)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Mannes Poel
    • 1
  • Job Zwiers
    • 1
  • Anton Nijholt
    • 1
  • Rudy de Jong
    • 1
  • Edward Krooman
    • 1
  1. 1.Dept. Computer ScienceUniversity of TwenteEnschedeThe Netherlands

Personalised recommendations