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Image based recognition of gaze direction using adaptive methods

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Gesture and Sign Language in Human-Computer Interaction (GW 1997)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1371))

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Abstract

Human-machine interfaces based on gaze recognition can greatly simplify the handling of computer applications. However, most of the existing systems have problems with changing environments and different users. As a solution we use (i) adaptive components which can be trained online and (ii) detect common facial features, i.e. eyes, nose and mouth, for gaze recognition. In a first step an adaptive color histogram segmentation method roughly determines the region of interest including the user’s face. Within this region we then use a hierarchical recognition approach to detect the facial features. In the last stage of our system these feature positions are used to estimate gaze direction by detailed analysis of the eye region. We achieve an average precision of 1.5 ‡ for the gaze pan and 2.5 ‡ for the tilt angle while the user looks on a computer screen. The system runs at a rate of one frame per second on a common workstation.

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References

  1. S. Baluja and D. Pomerleau: “Non-Intrusive Gaze Tracking Using Artificial Neural Networks”. In Advances in Neural Information Processing Systems (NIPS) 6., Ed. J.D. Cowan, G. Tesauro and J. Alspector, Morgan Kaufmann Publishers, San Francisco, CA., 1994.

    Google Scholar 

  2. H.O. Istance and P. Howarth: “Keeping an eye on your interface: The potential for eye-based control of graphical user interfaces”. In Proceedings of HCI’94, Cambridge University Press, August 1994.

    Google Scholar 

  3. R. J.K. Jacob: “Eye Tracking in Advanced Interface Design”. In Virtual Environments and Advanced Interface Design, Ed. W. Barfield and T.A. Furness, Oxford University Press, New York, USA, third edition, 1995, pages 258–288.

    Google Scholar 

  4. R. Kubisch and H. Ritter: “Erkennung menschlicher Kopfhaltungen mittels künstlicher neuronaler Netze”. In Informatik Aktuell, Mustererkennung 1996, Ed. B. Jähne et. al., Springer-Verlag, Berlin, Heidelberg, 1996, pages 109–117.

    Google Scholar 

  5. B. Schiele and A. Waibel: “Gaze Tracking Based on Face-Color”. In Int. Workshop on Automatic Face-and Gesture-Recognition, Zurich, Switzerland, June 1995.

    Google Scholar 

  6. A. Gee and R. Cipolla: “Determining the gaze of faces in images”. In Image and Vision Computing Volume 12 Number 10 December 1994, Butterworth-Heinemann Ltd., pages 639–647.

    Google Scholar 

  7. P. Ballard and G.C. Stockman: “Controlling a Computer via Facial Aspect”. In IEEE Trans. on Systems, Man, and Cybernetics, Vol. 25, No. 4, April 1995, pages 669–677.

    Article  Google Scholar 

  8. T. Horprasert, Y. Yacoob and L. S. Davis: “Computing 3-D Head Orientation from a Monocular Image Sequence”. In Proceedings of 2nd Intl. Conf. on Automatic Face & Gesture Recognition, Killington, Vermont, USA, 1996.

    Google Scholar 

  9. A. Drees: “Visuelle Erkennung von Handstellungen mit neuronalen Netzen”. PhD thesis, Universität Bielefeld, Technische Fakultät, September 1995.

    Google Scholar 

  10. M. Turk and A. Pentland: “Eigenfaces for Recognition”. In Journal of Cognitive Neuroscience, Vol. 3 No. 1, pages 71–86, 1997.

    Article  Google Scholar 

  11. A. Pentland, B. Moghaddam, T. Starner and M. Turk: “View-based and modular eigenspaces for face recognition”. In Proc. IEEE Computer Soc. Conf. on Computer Vision and Patt. Recog., 1994, pages 84–91.

    Google Scholar 

  12. H. Ritter: “Learning with the Self-Organizing Map”. In Artificial Neural Networks, Vol. 1, 1991, pages 379–384.

    Google Scholar 

  13. A. C. Varchmin, R. Rae and H. Ritter: “Facial feature detection using neural networks”. In Proceedings of the International Conference on Artificial Neural Networks ’97, 1997, pages 955–960.

    Google Scholar 

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Author information

Authors and Affiliations

  1. AG Neuroinformatik, Technische Fakultät, Universität Bielefeld, Postfach 100 131, D-33501, Bielefeld

    Axel Christian Varchmin, Robert Rae & Helge Ritter

Authors
  1. Axel Christian Varchmin
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  2. Robert Rae
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  3. Helge Ritter
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Corresponding author

Correspondence to Robert Rae .

Editor information

Ipke Wachsmuth Martin Fröhlich

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© 1998 Springer-Verlag

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Varchmin, A.C., Rae, R., Ritter, H. (1998). Image based recognition of gaze direction using adaptive methods. In: Wachsmuth, I., Fröhlich, M. (eds) Gesture and Sign Language in Human-Computer Interaction. GW 1997. Lecture Notes in Computer Science, vol 1371. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0053004

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  • DOI: https://doi.org/10.1007/BFb0053004

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64424-8

  • Online ISBN: 978-3-540-69782-4

  • eBook Packages: Springer Book Archive

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