We analyze Kinect as a 3D measuring device, experimentally investigate depth measurement resolution and error properties, and make a quantitative comparison of Kinect accuracy with stereo reconstruction from SLR cameras and a 3D-TOF camera. We propose a Kinect geometrical model and its calibration procedure providing an accurate calibration of Kinect 3D measurement and Kinect cameras. We compare our Kinect calibration procedure with its alternatives available on Internet, and integrate it into an SfM pipeline where 3D measurements from a moving Kinect are transformed into a common coordinate system, by computing relative poses from matches in its color camera.


Depth Image Depth Camera Kinect Camera Calibration Board Multiview Stereo 
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.



This research was supported by TA02011275—ATOM—Automatic Three-dimensional Terrain Monitoring and FP7-SPACE-241523 ProViScout grants.


  1. 1.
    Bouguet, J.Y.: Camera calibration toolbox. (2010)
  2. 2.
  3. 3.
    Dryanovski, I., Morris, W., Magnenat, S.: kinect_node. (2010)
  4. 4.
    Freedman, B., Shpunt, A., Machline, M., Arieli, Y.: Depth mapping using projected patterns. US Patent (2010) Google Scholar
  5. 5.
    Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2003) Google Scholar
  6. 6.
    Havlena, M., Torii, A., Pajdla, T.: Efficient structure from motion by graph optimization. doi: 10.1007/978-3-642-15552-9_8
  7. 7.
    Henry, P., Krainin, M., Herbst, E., Ren, X., Fox, D.: RGB-D mapping: using Kinect-style depth cameras for dense 3d modeling of indoor environments. Int. J. Robot. Res. (2012). doi: 10.1177/0278364911434148 Google Scholar
  8. 8.
    Herrera, D.C., Kannala, J., Heikkila, J.: Accurate and practical calibration of a depth and color camera pair. (2011)
  9. 9.
    Jancosek, M., Pajdla, T.: Multi-view reconstruction preserving weakly-supported surfaces. In: IEEE Conference on Computer Vision and Pattern Recognition (2011) Google Scholar
  10. 10.
    Khoshelham, K.: Accuracy analysis of Kinect depth data. In: ISPRS Workshop Laser Scanning, vol. XXXVIII (2011) Google Scholar
  11. 11.
    Konolige, K., Mihelich, P.: Technical description of Kinect calibration. (2011)
  12. 12.
    Lai, K., Bo, L., Ren, X., Fox, D.: Sparse distance learning for object recognition combining RGB and depth information. In: IEEE International Conference on Robotics and Automation (2011) Google Scholar
  13. 13.
    MESA Imaging: SwissRanger SR-4000. (2011)
  14. 14.
    Microsoft: Kinect for X-BOX 360. (2010)
  15. 15.
    Microsoft: Kinect for Windows. (2012)
  16. 16.
    Openni: (2011)
  17. 17.
    Shotton, J., Fitzgibbon, A., Cook, M., Sharp, T., Finocchio, M., Moore, R., Kipman, A., Blake, A.: Real-time human pose recognition in parts from a single depth image. In: IEEE Conference on Computer Vision and Pattern Recognition (2011) Google Scholar
  18. 18.
    Smisek, J., Jancosek, M., Pajdla, T.: 3D with Kinect. In: International Conference on Computer Vision—Workshop on Consumer Depth Cameras for Computer Vision (2011) Google Scholar
  19. 19.
    Smisek, J., Pajdla, T.: 3D camera calibration. M.Sc. thesis, Czech Technical University in Prague (2011) Google Scholar
  20. 20.
    Snavely, N., Seitz, S., Szeliski, R.: Modeling the world from internet photo collections. Int. J. Comput. Vis. (2007) Google Scholar
  21. 21.
  22. 22.
  23. 23.
    Willow Garage: ROS—Kinect calibration: code complete. (2010)
  24. 24.
    Willow Garage: Camera calibration and 3D reconstruction. (2011)
  25. 25.
    Willow Garage: Turtlebot. (2011)

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  1. 1.Center for Machine Perception, Dept. of Cybernetics, FEECzech Technical University in PraguePragueCzech Republic

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