SFM FOR PLANAR SCENES: A DIRECT AND ROBUST APPROACH

Fadi Dornaika, Angel D. Sappa

2005

Abstract

Traditionally, the Structure From Motion (SFM) problem has been solved using feature correspondences. This approach requires reliably detected and tracked features between images taken from widespread locations. In this paper, we present a new paradigm to the SFM problem for planar scenes. The novelty of the paradigm lies in the fact that instead of image feature correspondences, only image derivatives are used. We introduce two approaches. The first approach estimates the SFM parameters in two steps. The second approach directly estimates the parameters in one single step. Moreover, for both strategies we introduce the use of robust statistics in order to get robust solutions in presence of outliers. Experiments on both synthetic and real image sequences demonstrated the effectiveness of the developed methods.

References

  1. Brodsky, T. and Fermuller, C. (2002). Self-calibration from image derivatives. International Journal of Computer Vision, 48(2):91-114.
  2. Brooks, M., Chojnacki, W., and Baumela, L. (1997). Determining the egomotion of an uncalibrated camera from instantaneous optical flow. Journal of the Optical Society of America A, 14(10):2670-2677.
  3. Fischler, M. and Bolles, R. (1981). Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communication ACM, 24(6):381-395.
  4. Huber, P. (2003). Robust Statistics. Wiley.
  5. Jonathan, A., M., and Sclaroff, S. (2002). Recursive estimation of motion and planar structure. In IEEE Conference on Computer Vision and Pattern Recognition.
  6. Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P. (1992). Numerical Recipes in C. Cambridge University Press.
  7. Rousseeuw, P. and Leroy, A. (1987). Robust Regression and Outlier Detection. John Wiley & Sons, New York.
  8. Weng, J., Huang, T. S., and Ahuja, N. (1993). Motion and Structure from Image Sequences. Springer-Verlag, Berlin.
  9. Zucchelli, M., Jose, S., and Christensen, H. (2002). Multiple plane segmentation using optical flow. In British Machine Vision Conference.
Download


Paper Citation


in Harvard Style

Dornaika F. and D. Sappa A. (2005). SFM FOR PLANAR SCENES: A DIRECT AND ROBUST APPROACH . In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 972-8865-30-9, pages 175-180. DOI: 10.5220/0001173801750180


in Bibtex Style

@conference{icinco05,
author={Fadi Dornaika and Angel D. Sappa},
title={SFM FOR PLANAR SCENES: A DIRECT AND ROBUST APPROACH},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2005},
pages={175-180},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001173801750180},
isbn={972-8865-30-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - SFM FOR PLANAR SCENES: A DIRECT AND ROBUST APPROACH
SN - 972-8865-30-9
AU - Dornaika F.
AU - D. Sappa A.
PY - 2005
SP - 175
EP - 180
DO - 10.5220/0001173801750180