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Statistical Modeling of Interpersonal Distance with Range Imaging Data

  • René Hempel
  • Patrick Westfeld
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5398)

Abstract

The presented work combines automated highly resolved spatio-temporal photogrammetric data acquisition and analysis with statistical approaches for the determination of the interpersonal distance between interacting persons. This topic forms an interesting bridge between engineering and educational research, delivering a new efficient measurement technique to educational research and opening new application fields to photogrammetry.

Keywords

Interpersonal Distance Range Imaging Data Image Sequence Analysis Body Models Time Series Models 

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References

  1. 1.
    Amann, H., Escher, J.: Analysis I. Birkhäuser, Basel (2002)CrossRefzbMATHGoogle Scholar
  2. 2.
    Ackermann, F.: High Precision Digital Image Correlation. In: Proceedings of the 39th Photogrammetric Week, vol. 9, pp. 231–243 (1984)Google Scholar
  3. 3.
    Aiello, J.R.: A further look at equilibrium theory: Visual interaction as a function of interpersonal distance. Environmental Psychology and Nonverbal Behavior 1(2), 122–140 (1977)CrossRefGoogle Scholar
  4. 4.
    Aiello, J.R., De Carlo Aiello, T.: The development of personal space: proxemic behavior of children 6 through 16. Human Ecology 2(3), 177–189 (1974)CrossRefGoogle Scholar
  5. 5.
    Argyle, M., Dean, J.: Eye-contact, distance and affiliation. Sociometry 28(3), 289–304 (1965)CrossRefGoogle Scholar
  6. 6.
    Ballard, D.H., Brown, C.M.: Computer Vision. Prentice-Hall, Englewood Cliffs (1982)Google Scholar
  7. 7.
    Bollerslev, T.P.: Generalized autoregressive conditional heteroscedasticity. Journal of Econometrics 31, 143–327 (1986)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Box, G.E.P., Jenkins, G.M.: Time Series Analysis - Forecasting and Control. Holden Day (1970)Google Scholar
  9. 9.
    Brockwell, J.P., Davis, R.A.: Time Series: Theory and Methods, 2nd edn. Springer, Heidelberg (1991)CrossRefzbMATHGoogle Scholar
  10. 10.
    Du, H., Oggier, T., Lustenberger, F., Charbon, E.: A Virtual Keyboard Based on True-3D Optical Ranging. In: British Machine Vision Conference 2005, pp. 220–229 (2005)Google Scholar
  11. 11.
    Durbin, J., Koopman, S.: Time Series Analysis by State Space Methods. Clarendon Press (2001)Google Scholar
  12. 12.
    Engle, R.F.: Autoregressive heterscedasticity with estimates of the variance of U.K. inflation. Econometrica 50, 987–1008 (1982)MathSciNetCrossRefzbMATHGoogle Scholar
  13. 13.
    Granger, C.W.J., Joyeux, R.: An introduction to Long-Memory Time Series Models and fractional differencing. Journal of Time Series Analysis 1, 1–15 (1980)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Gouriéroux, C.: ARCH Models and Financial Applications. Springer, Heidelberg (1997)CrossRefzbMATHGoogle Scholar
  15. 15.
    Gudmundsson, S.A.: Robot Vision Applications using the CSEM SwissRanger Camera. Informatics and Mathematical Modelling, Technical University of Denmark, Master’s thesis (2006)Google Scholar
  16. 16.
    Hall, E.T.: Die Sprache des Raumes. Pädagogischer Verlag Schwann (1976)Google Scholar
  17. 17.
    Hamilton, J.D.: Time Series Analysis. Princeton University Press, Princeton (1994)zbMATHGoogle Scholar
  18. 18.
    Hoerl, A., Kennard, R.: Ridge Regression: Biased Estimation for Nonorthogonal Problems. Technometrics 12, 55–67 (1970a)CrossRefzbMATHGoogle Scholar
  19. 19.
    Hoerl, A., Kennard, R.: Ridge Regression: Applications to Nonorthogonal Problems. Technometrics 12, 69–82 (1970b)CrossRefzbMATHGoogle Scholar
  20. 20.
    Hoerl, A., Kennard, R.: Ridge Regression: Iterative Estimation of the Biasing Parameter. Communications in Statistics A 5, 77–88 (1970b)CrossRefzbMATHGoogle Scholar
  21. 21.
    Hosking, J.R.M.: Fractional differencing. Biometrica 68, 165–176 (1981)MathSciNetCrossRefzbMATHGoogle Scholar
  22. 22.
    Mesa Imaging, A.G.: Zurich, SwitzerlandGoogle Scholar
  23. 23.
    Magnus, J.R., Neudecker, H.: Matrix Differential Calculus with Applications in Statistics and Econometrics. Wiley & Sons, Chichester (1999)zbMATHGoogle Scholar
  24. 24.
    Patterson, M.L.: A sequential functional model of nonverbal exchange. Psychological Review 89(3), 231–249 (1982)CrossRefGoogle Scholar
  25. 25.
    Patterson, M.L.: Nonverbal behavior. A functional perspective. Springer, Heidelberg (1983)CrossRefGoogle Scholar
  26. 26.
    Patterson, M.L.: Intimacy, social control, and nonverbal involvement: A functional approach. In: Derlega, V. (ed.) Communication, intimacy, and close relationships, pp. 105–132. Academic Press, Inc., New York (1984)CrossRefGoogle Scholar
  27. 27.
    Ramsay, J.O., Silverman, B.W.: Functional data analysis, 2nd edn. Springer, Heidelberg (2005)zbMATHGoogle Scholar
  28. 28.
    Sommer, R.: Personal space. The behavioral basis of design. Prentice-Hall, Englewood Cliffs (1969)Google Scholar
  29. 29.
    Westfeld, P.: Development of Approaches for 3-D Human Motion Behaviour Analysis Based on Range Imaging Data. Optical 3-D Measurement Techniques VIII, II, pp. 393–402 (2007)Google Scholar
  30. 30.
    Westfeld, P., Hempel, R.: Range Image Sequence Analysis by 2.5-D Least Squares Tracking with Variance Component Estimation and Robust Variance Covariance Matrix Estimation. In: International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Part B5, vol. XXXVII, pp. 457–462 (2008)Google Scholar
  31. 31.
    Zywitza, F., Massen, J., Brunn, M., Lang, C., Görnig, T.: One-to-Three-dimensional Ranging for Future Automotive Safety Systems. In: Proceedings of the 1st Range Imaging Research Day at ETH Zurich in Switzerland (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • René Hempel
    • 1
  • Patrick Westfeld
    • 2
  1. 1.Faculty of EducationTechnische Universität DresdenDresdenGermany
  2. 2.Institute of Photogrammetry and Remote SensingTechnische Universität DresdenDresdenGermany

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