Error Analysis of Feature Based Disparity Estimation

  • Patrick A. Mikulastik
  • Hellward Broszio
  • Thorsten Thormählen
  • Onay Urfalioglu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4319)


For real-time disparity estimation from stereo images the coordinates of feature points are evaluated. This paper analyses the influence of camera noise on the accuracy of feature point coordinates of a feature point detector similar to the Harris Detector, modified for disparity estimation. As a result the error variance of the horizontal coordinate of each feature point and the variance of each corresponding disparity value is calculated as a function of the image noise and the local intensity distribution. Disparities with insufficient accuracy can be discarded in order to ensure a given accuracy. The results of the error analysis are confirmed by experimental results.


Error Variance Feature Point Image Noise Feature Detector Stereo Image 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Luxen, M.: Variance component estimation in performance characteristics applied to feature extraction procedures. In: Michaelis, B., Krell, G. (eds.) DAGM 2003. LNCS, vol. 2781, pp. 498–506. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  2. 2.
    Rohr, K.: Localization properties of direct corner detectors. Journal of Mathematical Imaging and Vision 4, 139–150 (1994)CrossRefMathSciNetGoogle Scholar
  3. 3.
    Szeliski, R.: Bayesian Modeling of Uncertainty in Low-Level Vision. Kluwer International Series in Engineering and Computer Science 79 (1989) ISBN: 0792390393 Google Scholar
  4. 4.
    Shi, J., Tomasi, C.: Good features to track. In: CVPR, pp. 593–600. IEEE, Los Alamitos (1994)Google Scholar
  5. 5.
    Kanazawa, Y., Kanatani, K.: Do we really have to consider covariance matrices for image features? In: ICCV, pp. 301–306 (2001)Google Scholar
  6. 6.
    Morris, D.D., Kanade, T.: A unified factorization algorithm for points, line segments and planes with uncertainty models. In: Proceedings of Sixth IEEE International Conference on Computer Vision (ICCV 1998), pp. 696–702 (1998)Google Scholar
  7. 7.
    Singh, A.: An estimation-theoretic framework for image-flow computation. In: ICCV. Third international conference on computer vision, pp. 168–177 (1990)Google Scholar
  8. 8.
    Förstner, W.: Reliability analysis of parameter estimation in linear models with applications to mensuration problems in computer vision. In: CVGIP, vol. 40, pp. 273–310 (1987)Google Scholar
  9. 9.
    Harris, C., Stephens, M.: A combined corner and edge detector. In: 4th Alvey Vision Conference, pp. 147–151 (1988)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Patrick A. Mikulastik
    • 1
  • Hellward Broszio
    • 1
  • Thorsten Thormählen
    • 1
  • Onay Urfalioglu
    • 1
  1. 1.Information Technology LaboratoryUniversity of HannoverGermany

Personalised recommendations