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Using Human Motion Intensity as Input for Urban Design

  • Esben S. Poulsen
  • Hans J. Andersen
  • Rikke Gade
  • Ole B. Jensen
  • Thomas B. Moeslund
Part of the Communications in Computer and Information Science book series (CCIS, volume 277)

Abstract

This paper presents a study investigating the potential use of human motion intensities as input for parametric urban design. Through a computer vision analysis of thermal images, motion intensity maps are generated and utilized as design drivers for urban design patterns; and, through a case study of a town square, human occupancy and motion intensities are used to generate situated flow topologies presenting new adaptive methods for urban design. These methods incorporate local flow as design drivers for canopy, pavement and furniture layout. The urban design solution may be configured due to various parameters such as security, comfort, navigation, efficiency, or aesthetics.

Keywords

Urban Space Urban Design Motion Intensity Design Scenario Human Activity Recognition 
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.

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References

  1. 1.
    Bertozzi, M., Broggi, A., Caraffi, C., Rose, M.D., Felisa, M., Vezzoni, G.: Pedestrian detection by means of far-infrared stereo vision. Computer Vision and Image Understanding 106(2-3), 194–204 (2007), http://www.sciencedirect.com/science/article/pii/S1077314206001858; Special issue on Advances in Vision Algorithms and Systems beyond the Visible Spectrum Google Scholar
  2. 2.
    Davis, J., Sharma, V.: Robust detection of people in thermal imagery. In: Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, vol. 4, pp. 713–716 (August 2004)Google Scholar
  3. 3.
    Gehl, J.: Cities for people. Island Press, Washington, DC (2010)Google Scholar
  4. 4.
    Hajer, M., Reijndorp, A.: search of New Public Domain. Nai Publishers, Rotterdam (2001)Google Scholar
  5. 5.
    Han, J., Bhanu, B.: Human activity recognition in thermal infrared imagery. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPR Workshops, p. 17 (June 2005)Google Scholar
  6. 6.
    Hensel, M., Menges, A.: Morpho-ecologies. Architectural Association, London (2006)Google Scholar
  7. 7.
    Jensen, O.B.: Facework, flow and the city - simmel, goffman and mobility in the contemporary city. Mobilities 2(2), 143–165 (2006)CrossRefGoogle Scholar
  8. 8.
    Jensen, O.B.: Flows of meaning, cultures of movements - urban mobility as meaningful everyday life practice. Mobilities 4(4), 139–158 (2009)CrossRefGoogle Scholar
  9. 9.
    Jensen, O.B.: Erving Goffman and Everyday Life Mobility, ch. 14, pp. 333–351. Routledge (2010)Google Scholar
  10. 10.
    Jensen, O.B.: Negotiation in motion: Unpacking a geography of mobility. Space and Culture 13(4), 389–402 (2010)CrossRefGoogle Scholar
  11. 11.
    Kolarevic, B., Malkawi, A.: Performative architecture: beyond instrumentality. Spon Press, New York (2005)Google Scholar
  12. 12.
    Laursen, E.V., Rosenørn, S.: Technical Report 2-25: New hours of bright sunshine normals for Denmark, 1961-1990. Danish Meteorological Institute (2002), http://www.dmi.dk/dmi/tr02-25.pdf, ISSN 0906-897X, ISSN (online) 1399-1388
  13. 13.
    Lynch, K.: Good City Form. MIT Press, Cambridge (1981)Google Scholar
  14. 14.
    Lynn, G.: Animate form. Princeton Architectural Press, New York (1999)Google Scholar
  15. 15.
    McCullough, M.: Digital ground: architecture, pervasive computing, and environmental knowing. MIT Press, Cambridge (2005)Google Scholar
  16. 16.
    Schumacher, P.: Parametricism and the Autopoiesis of Architecture. Log 11, Los Angeles, lecture, SCI, Arc (September 2010), http://www.patrikschumacher.com/Texts/Parametricism%20and%20the%20Autopoiesis%20of%20Architecture.html
  17. 17.
    Schumacher, P.: The autopoiesis of architecture: A new framework for architecture, vol. 1. Wiley (2011)Google Scholar
  18. 18.
    Spuybroek, L.: NOX: machining architecture. Thames and Hudson, London (2004)Google Scholar
  19. 19.
    Terzidis, K.: Algorithmic Architecture. Architectural Press, Oxford (2006)Google Scholar
  20. 20.
    Whyte, W.: City. Rediscovering the Center. University of Pennsylvania Press, Philadelphia (1988/2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Esben S. Poulsen
    • 1
  • Hans J. Andersen
    • 1
  • Rikke Gade
    • 1
  • Ole B. Jensen
    • 1
  • Thomas B. Moeslund
    • 1
  1. 1.Department of Architecture, Design and Media TechnologyAalborg UniversityDenmark

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