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Thermal 3D Mapping of Building Façades

  • Dorit BorrmannEmail author
  • Jan Elseberg
  • Andreas Nüchter
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 193)

Abstract

Never before in history were humans as dependant on energy as we are today. But the natural ressources are limited and a waste of energy has drastic influences on the environment. In their Action Plan for Energy Efficiency [6] the European Commission estimates that the largest and cost-effictive energy savings potential lies in residential (≈ 27%) and commercial (≈ 30%) buildings. To eliminate heat and air conditioning losses in buildings and factories heat and air leaks need to be localized and identified. Imagine the availability of a complete 3D model of every building that architects can use to analyze the heat insulation of buildings and to identify necessary modifications. In these 3D models temperature peaks are not only detectable but also their extent is visible. A robot equiped with a 3D laser scanner, a thermal camera, and a color camera constitutes the basis for our approach. The data from all three sensors and from different locations are joined into one high-precise 3D model that shows the heat distribution. This paper describes the setup of the hardware and the methods applied to create the 3D model, including the automatic co-calibration of the sensors. Challenges unique to the task of thermal mapping of outdoor environments are discussed.

Keywords

Point Cloud Terrestrial Laser Scanning Thermal Camera Structure From Motion Calibration Pattern 
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.
    Alba, M.I., Barazzetti, L., Scaioni, M., Rosina, E., Previtali, M.: Mapping infrared data on terrestrial laser scanning 3D models of buildings. Remote Sensing 3(9), 1847–1870 (2011)CrossRefGoogle Scholar
  2. 2.
    Nüchter, A., et al.: 3DTK – The 3D Toolkit (2011), http://slam6d.sourceforge.net/
  3. 3.
    Bradski, G., Kaehler, A.: Learning OpenCV, Computer Vision with OpenCV library, 1st edn. O’Reilly Media (2008)Google Scholar
  4. 4.
    Brenner, C., Dold, C., Ripperda, N.: Coarse orientation of terrestrial laser scans in urban environments. ISPRS Journal of Photogrammetry and Remote Sensing 63(1), 4–18 (2008)CrossRefGoogle Scholar
  5. 5.
    Cabrelles, M., Galcera, S., Navarro, S., Lerma, J.L., Akasheh, T., Haddad, N.: Integration of 3D laser scanning, photogrammetry and thermography to record architectural monuments. In: Proceedings of the 22nd CIPA Symposium, Kyoto, Japan (2009)Google Scholar
  6. 6.
    Commission of the European Communities. Addressing the challenge of energy efficiency through Information and Communication Technologies. Communications to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions, COM(2008) 241 final (May 2008)Google Scholar
  7. 7.
    Furukawa, Y., Ponce, J.: Accurate, dense, and robust multi-view stereopsis. IEEE PAMI 32(8), 1362–1376 (2010)CrossRefGoogle Scholar
  8. 8.
    Högner, L., Stilla, U.: Texture extraction for building models from ir sequences of urban areas. In: Proc. of 2007 Joint Event: URBAN / URS (2007)Google Scholar
  9. 9.
    Iwaszczuk, D., Hoegner, L., Stilla, U.: Matching of 3D building models with IR images for texture extraction. In: Joint Urban Remote Sensing Event, Munich, Germany (2011)Google Scholar
  10. 10.
    Luhmann, T., Piechel, J., Ohm, J., Roelfs, T.: Geometric calibration of thermographic cameras. Intern. Archives of Photogrammetry, Remote Sensing and Spatial Information 38(pt. 5) (2010)Google Scholar
  11. 11.
    Nüchter, A.: 3D Robotic Mapping: The Simultaneous Localization and Mapping Problem with Six Degrees of Freedom. Tracts in Advanced Robotics, vol. 52. Springer (2009)Google Scholar
  12. 12.
    Pelagottia, A., Del Mastio, A., Uccheddu, F., Remondino, F.: Automated multispectral texture mapping of 3d models. In: EUSIPCO 2009, Glasgow, Scotland (2009)Google Scholar
  13. 13.
    Prakash, S., Pei, L.Y., Caelli, T.: 3d mapping of surface temperature using thermal stereo. In: Proc. ICARCV (2006)Google Scholar
  14. 14.
    Project Webpage. Project ThermalMapper (2011), http://www.faculty.jacobs-university.de/anuechter/thermalmapper.html
  15. 15.
    Snavely, N., Seitz, S.M., Szeliski, R.: Photo tourism: Exploring image collections in 3d. ACM Transactions on Graphics (Proceedings of SIGGRAPH 2006) (2006)Google Scholar
  16. 16.
    Surmann, H., Nüchter, A., Hertzberg, J.: An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments. Journal Robotics and Autonomous Systems (JRAS) 45(3-4), 181–198 (2003)CrossRefGoogle Scholar
  17. 17.
    Wardlaw, J., Gryka, M., Wanner, F., Brostow, G., Kautz, J.: A new approach to thermal imaging visualisation. EngD Group Project, University College London (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Dorit Borrmann
    • 1
    Email author
  • Jan Elseberg
    • 1
  • Andreas Nüchter
    • 1
  1. 1.Jacobs University Bremen gGmbHBremenGermany

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