AN EFFICIENT CATADIOPTRIC SENSOR CALIBRATION BASED ON A LOW-COST TEST-PATTERN

N. Ragot, J. Y. Ertaud, X. Savatier, B. Mazari

2006

Abstract

This article presents an innovative calibration method for a panoramic vision sensor which is dedicated to the three-dimensional reconstruction of an environment with no prior knowledge. We begin this paper by a detailed presentation of the architecture of the sensor. We mention the general features about central catadioptric sensors and we clarify the fixed viewpoint constraint. Next, a large description of the previous panoramic calibration techniques is given. We mention the different postulates which lead us to envisage the method of calibration presented in this paper. A description of the low-cost calibration test pattern is given. The algorithmic approach developed is detailed. We present the results obtained. Finally, the last part is devoted to the result reviewing.

References

  1. Aliaga, D. (2001). Accurate catadioptric calibration for real-time pose estimation inroom-size environments. In 8th IEEE International Conference on Computer Vision, volume 1, pages 127-134.
  2. C. Cauchois, E. Brassart, C. P. and Clerentin, A. (1999). Technique for calibrating an omnidirectional sensor. In International Conference on Intelligent Robots and Systems.
  3. C. Drocourt, L. Delahoche, E. B. and Cauchois, C. (2001). Simultaneous localization and map building paradigm based on omnidirectional stereoscopic vision. In Proceeding IEEE Workshop on Omnidirectional Vision Applied to Robotic Orientation and Nondestructive Testing, pages 73-79.
  4. C. Geyer, K. D. (2001). Catadioptric projective geometry. International Journal of Computer Vision, 43:223- 243.
  5. F. Marzani, Y. Voisin, A. D. and Voon, L. F. L. Y. (2002). Calibration of a 3d reconstruction system using a structured light source. Journal of Optical Engineering, 41:484-492.
  6. Faugeras, O. (1993). Three-dimensional computer vision : a geometric viewpoint. MIT Press, Cambridge, Massachusetts, 4th edition.
  7. G.L. Mariottini, D. P. (2005). The epipolar geometry toolbox : multiple view geometry for visual servoing for matlab. IEEE Robotics and Automation Magazine.
  8. J. Fabrizio, J.-P. Tarel, R. B. (2002). Calibration of panoramic catadioptric sensors made easier. In Workshop on Omnidirectional Vision.
  9. J.P. Barreto, H. A. (2005). Geometric properties of central catadioptric line images and their application in calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27:1327-1333.
  10. Kang, S. (2000). Catadioptric self-calibration. In International Conference on Computer Vision and Pattern Recognition, volume 1, pages 201-207.
  11. L. Smadja, R. Benosman, J. D. (2004). Cylindrical sensor calibration using lines. In 5th Workshop on Omnidirectional Vision, Camera Networks and Non-Classical Cameras, pages 139-150.
  12. Lacroix, S., Gonzalez, J., El Mouaddib, M., Vasseur, P., Labbani, O., Benosman, R., Devars, J., and Fabrizio, J. (2005). Vision omnidirectionnelle et robotique. rapport final. Technical report, LAAS, CREA, LISIF.
  13. Moldovan, D. (2004). A geometrically calibrated pinhole model for single viewpoint omnidirectional imaging systems. In British Machine Vision Conference.
  14. Mouaddib, M. E. (2005). La vision omnidirectionnelle. In Journée Nationale de la Recherche en Robotique.
  15. P. Biber, H. Andreasson, T. D. and Andreas, A. S. (2004). 3d modeling of indoor environments by a mobile robot with a laser scanner and panoramic camera. In IEEE/RSJ International Conference on Intelligent Robots and Systems.
  16. S. Baker, S. N. (1999). A theory of single-viewpoint catadioptric image formation. International Journal of Computer Vision, 35:175-196.
  17. S. Baker, S. N. (2001). Panoramic Vision: Sensors, Theory and Applications, chapter Single viewpoint catadioptric cameras, pages 39-73. Springer-Verlag, 1st edition.
  18. Svoboda, T. (1999). Central panoramic cameras. Design, geometry, egomotion. PhD thesis, Czech Technical Univeristy.
  19. T. Ea, O. Romain, C. G. and Garda, P. (2001). Un capteur de sphéréo-vision stéréoscopique couleur. In Congrès francophone de vision par ordinateur ORASIS.
  20. T. Svoboda, T. Pajdla, V. H. (1998). Epipolar geometry for panoramic cameras. In 5th European Conference on Computer Vision, volume 1406, pages 218-232.
  21. X. Ying, Z. H. (2003). Catadioptric camera calibration using geometric invariants. In International Conference on Computer Vision, pages 1351-1358.
  22. Zhu, Z. (2001). Omnidirectional stereo vision. In 10th IEEE ICAR Workshop on Omnidirectional Vision.
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Paper Citation


in Harvard Style

Ragot N., Y. Ertaud J., Savatier X. and Mazari B. (2006). AN EFFICIENT CATADIOPTRIC SENSOR CALIBRATION BASED ON A LOW-COST TEST-PATTERN . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 972-8865-40-6, pages 11-18. DOI: 10.5220/0001374100110018


in Bibtex Style

@conference{visapp06,
author={N. Ragot and J. Y. Ertaud and X. Savatier and B. Mazari},
title={AN EFFICIENT CATADIOPTRIC SENSOR CALIBRATION BASED ON A LOW-COST TEST-PATTERN},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2006},
pages={11-18},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001374100110018},
isbn={972-8865-40-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - AN EFFICIENT CATADIOPTRIC SENSOR CALIBRATION BASED ON A LOW-COST TEST-PATTERN
SN - 972-8865-40-6
AU - Ragot N.
AU - Y. Ertaud J.
AU - Savatier X.
AU - Mazari B.
PY - 2006
SP - 11
EP - 18
DO - 10.5220/0001374100110018