Advertisement

Noise Modelling and Uncertainty Propagation for TOF Sensors

  • Amira Belhedi
  • Adrien Bartoli
  • Steve Bourgeois
  • Kamel Hamrouni
  • Patrick Sayd
  • Vincent Gay-Bellile
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7585)

Abstract

Time-of-Flight (TOF) cameras are active real time depth sensors. One issue of TOF sensors is measurement noise. In this paper, we present a method for providing the uncertainty associated to 3D TOF measurements based on noise modelling. Measurement uncertainty is the combination of pixel detection error and sensor noise. First, a detailed noise characterization is presented. Then, a continuous model which gives the noise’s standard deviation for each depth-pixel is proposed. Finally, a closed-form approximation of 3D uncertainty from 2D pixel detection error is presented. An applicative example is provided that shows the use of our 3D uncertainty modelling on real data.

Keywords

Noise Modelling Depth Image Depth Measurement Uncertainty Propagation Sensor Noise 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Lange, R.: 3D Time-of-Flight distance measurement with custom solid-state image sensors in CMOS/CCD-technology. PhD thesis, University of Siegen, Germany (2000)Google Scholar
  2. 2.
    Kim, S.Y., Cho, J.H., Koschan, A., Abidi, M.A.: Spatial and temporal enhancement of depth images captured by a time-of-flight depth sensor. In: ICPR (2010)Google Scholar
  3. 3.
    Kim, S.M., Cha, J., Ryu, J., Lee, K.H.: Depth video enhancement for haptic interaction using a smooth surface reconstruction. IEICE - Trans. Inf. Syst. E89-D, 37–44 (2006)CrossRefGoogle Scholar
  4. 4.
    Cho, J.H., Chang, I.Y., Kim, S., Lee, K.: Depth image processing technique for representing human actors in 3dtv using single depth camera. In: 3DTV (2007)Google Scholar
  5. 5.
    Zhu, J., Wang, L., Yang, R., Davis, J.: Fusion of time-of-flight depth and stereo for high accuracy depth maps. In: CVPR (2008)Google Scholar
  6. 6.
    Chambers, J.M., Cleveland, W.S., Kliener, B., Tukey, P.A.: Graphical Methods for Data Analysis. Wadsworth (1983)Google Scholar
  7. 7.
    May, S., Droeschel, D., Holz, D., Fuchs, S.: Three-dimensional mapping with time-of-flight cameras. J. Field Robot. 26, 934–964 (2009)CrossRefGoogle Scholar
  8. 8.
  9. 9.
    Karel, W., Dorninger, P., Pfeifer, N.: In situ determination of range camera quality parameters by segmentation. In: Opt. 3D Meas. Tech. (2007)Google Scholar
  10. 10.
    Guömundsson, S.A., Aanæs, H., Larsen, R.: Environmental effects on measurement uncertainties of Time-of-Fight cameras. In: ISSCS (2007)Google Scholar
  11. 11.
    Weyer, C.A., Bae, K.H., Lim, K., Lichti, D.D.: Extensive metric performance evaluation of a 3D range camera. In: ISPRS (2008)Google Scholar
  12. 12.
    Belhedi, A., Bourgeois, S., Gay-Bellile, V., Sayd, P., Bartoli, A., Hamrouni, K.: Non-parametric depth calibration of a tof camera. In: ICIP (2012)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Amira Belhedi
    • 1
    • 2
    • 3
  • Adrien Bartoli
    • 2
  • Steve Bourgeois
    • 1
  • Kamel Hamrouni
    • 3
  • Patrick Sayd
    • 1
  • Vincent Gay-Bellile
    • 1
  1. 1.LIST, LVICCEAFrance
  2. 2.ISITClermont Université, Université d’AuvergneFrance
  3. 3.ENIT, SITIUniversité de Tunis El ManarTunisia

Personalised recommendations