ESTIMATING CAMERA ROTATION PARAMETERS FROM A BLURRED IMAGE

Giacomo Boracchi, Vincenzo Caglioti, Alberto Danese

2008

Abstract

A fast rotation of the camera during the image acquisition results in a blurred image, which typically shows curved smears. We propose a novel algorithm for estimating both the camera rotation axis and the camera angular speed from a single blurred image. The algorithm is based on local analysis of the blur smears. Contrary to the existing methods, we treat the more general case where the rotation axis can be not orthogonal to the image plane, taking into account the perspective effects that in such case affect the smears. The algorithm is validated in experiments with synthetic and real blurred images, providing accurate estimates.

References

  1. Ballard, D. H. (1987). Generalizing the hough transform to detect arbitrary shapes. In Readings in Computer Vision: Issues, Problems, Principles, and Paradigms, pages 714-725. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.
  2. Bertero, M. and Boccacci, P. (1998). Introduction to Inverse Problems in Imaging. Institute of Physics Publishing.
  3. Donoho, D. L. and Johnstone, I. M. (1994). Ideal spatial adaptation by wavelet shrinkage. Biometrika, 81(3):425-455.
  4. Farid, H. and Simoncelli, E. (2004). Differentiation of discrete multi-dimensional signals. IEEE Transactions on Image Processing, 13(4):496-508.
  5. Harris, C. and Stephens, M. (1988). A combined corner and edge detector. In Proceedings of the 4th Alvey Vision Conference,, pages 147-151.
  6. Hong, H. and Zhang, T. (2003). Fast restoration approach for rotational motion blurred image based on deconvolution along the blurring paths. Optical Engineering, 42:347-3486.
  7. Klein, G. and Drummond, T. (2005). A single-frame visual gyroscope. In Proc. British Machine Vision Conference (BMVC'05), volume 2, pages 529-538, Oxford. BMVA.
  8. Ribaric, S., Milani, M., and Kalafatic, Z. (2000). Restoration of images blurred by circular motion. In Image and Signal Processing and Analysis, 2000. IWISPA 2000. Proceedings of the First International Workshop on, pages 53-60.
  9. Rothwell, C., Zisserman, A., Marinos, C., Forsyt h, D., and Mundy, J. (1992). Relative motion and pose from arbitrary plane curves. IVC, 10:250-262.
  10. Yitzhaky, Y. and Kopeika, N. S. (1996). Identification of blur parameters from motion-blurred images. In Tescher, A. G., editor, Proc. SPIE Vol. 2847, p. 270- 280, Applications of Digital Image Processing XIX, Andrew G. Tescher; Ed., pages 270-280.
Download


Paper Citation


in Harvard Style

Boracchi G., Caglioti V. and Danese A. (2008). ESTIMATING CAMERA ROTATION PARAMETERS FROM A BLURRED IMAGE . In Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008) ISBN 978-989-8111-21-0, pages 389-395. DOI: 10.5220/0001085403890395


in Bibtex Style

@conference{visapp08,
author={Giacomo Boracchi and Vincenzo Caglioti and Alberto Danese},
title={ESTIMATING CAMERA ROTATION PARAMETERS FROM A BLURRED IMAGE},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)},
year={2008},
pages={389-395},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001085403890395},
isbn={978-989-8111-21-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)
TI - ESTIMATING CAMERA ROTATION PARAMETERS FROM A BLURRED IMAGE
SN - 978-989-8111-21-0
AU - Boracchi G.
AU - Caglioti V.
AU - Danese A.
PY - 2008
SP - 389
EP - 395
DO - 10.5220/0001085403890395