Assessment of stereo camera calibration techniques for a portable mobile mapping system

Assessment of stereo camera calibration techniques for a portable mobile mapping system

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Mobile mapping systems that detect and geo-reference road markings almost always consist of a stereo camera system integrated with a global positioning system/inertial navigation system. The data acquired by this navigational system allows features detected in the stereo images to be assigned global co-ordinates. An essential step in this process is the calibration of the cameras, as it relates the pose of the two cameras to each other and a world co-ordinate system. In Europe, road markings must be evaluated from a 35 m range, so the cameras are required to have a wide field of view. Traditional calibration methods supposedly require a calibration object that would fill most of the calibration images. This large field of view would require a calibration object of substantial size that would be impractical for the purposes of this portable system. This study explores the theory of camera calibration and then details two camera calibration techniques (using portable 3D and 2D calibration objects). The accuracy of these methods is then evaluated using a ground-truth experiment.


    1. 1)
      • 1. El-Sheimy, N., Schwartz, K.P.: ‘Navigating urban areas by VISAT – a mobile mapping system integrating GPS/INS/digital cameras for GIS applications’, Navig., Inst. Navig. (IoN), 1999, 45, (4), pp. 275285.
    2. 2)
      • 2. El-Sheimy, N., Schwarz, K.P., Wei, M., Lavigne, M.: ‘VISAT: a mobile city survey system of high accuracy’. Eighth Int. Technical Meeting of the Satellite Division of the Institute of Navigation (ION95), Palm Springs, California, 1995, pp. 13071315.
    3. 3)
      • 3. Ellum, C., El-Sheimy, N.: ‘Land-based mobile mapping systems’, Photogramm. Eng. Remote Sens., 2002, 68, (1), pp. 1328.
    4. 4)
      • 4. Murray, S., Haughey, S., Brogan, M., Fitzgerald, C., McLoughlin, S., Deegan, C.: ‘Mobile mapping system for the automated detection and analysis of road delineation’, IET Intell. Transp. Syst., 2011, 5, (4), pp. 221230 (doi: 10.1049/iet-its.2010.0105).
    5. 5)
      • 5. Hartley, R., Zisserman, A.: ‘Multiple view geometry in computer vision’ (Cambridge University Press, 2nd edn.), 2003.
    6. 6)
      • 6. Zhang, Z.: ‘A flexible new technique for camera calibration’, IEEE Trans. Pattern Anal. Mach. Intell., 2000, 22, (11), pp. 13301334 (doi: 10.1109/34.888718).
    7. 7)
      • 7. Trucco, E., Verri, A.: ‘Introductory techniques for 3-D computer vision’ (Prentice-Hall, 1998, 1st edn.).
    8. 8)
      • 8. Bradski, G., Kaehler, A.: ‘Learning OpenCV: computer vision with the OpenCV library’ (O'Reilly Media, Inc., 1st edn.), 2008.
    9. 9)
      • 9. Loaiza, M.E., Raposo, A.B., Gattass, M.: ‘Multi-camera calibration based on an invariant pattern’, Comput. Graph., 2011, 35, pp. 198207 (doi: 10.1016/j.cag.2010.12.007).
    10. 10)
      • 10. Baronti, L., Dellepiane, M., Scopigno, R.: ‘Using Lego pieces for camera calibration: a preliminary study’. Proc. Eurographics Conf. 2010 – Short Papers, Norrköping, Sweden, 2010, pp. 97100.
    11. 11)
      • 11. Maybank, S., Faugeras, O.: ‘A theory of self-calibration of a moving camera’, Int. J. Comput. Vis., 1992, 8, (2), pp. 123151 (doi: 10.1007/BF00127171).
    12. 12)
      • 12. He, B.W., Li, Y.F.: ‘Camera calibration from vanishing points in a vision system’, Opt. Laser Technol., 2008, 50, pp. 555561 (doi: 10.1016/j.optlastec.2007.09.001).
    13. 13)
      • 13. Cao, X., Foroosh, H.: ‘Camera calibration and light source orientation from solar shadows’, Comput. Vis. Image Underst., 2007, 105, pp. 6072 (doi: 10.1016/j.cviu.2006.08.003).
    14. 14)
      • 14. Zhang, Z.: ‘Camera calibration with one-dimensional object’, IEEE Trans. Pattern Anal. Mach. Intell., 2004, 26, (7), pp. 892899 (doi: 10.1109/TPAMI.2004.21).
    15. 15)
      • 15. Cerveri, P., Borghese, N.A.: ‘Complete calibration of a stereo photogrammetric system through control points of unknown coordinates’, J. Biomech., 1998, 31, (1998), pp. 935940 (doi: 10.1016/S0021-9290(98)00104-3).
    16. 16)
      • 16. Guiducci, A.: ‘Camera calibration for road applications’, Comput. Vis. Image Underst., 2000, 79, pp. 250266 (doi: 10.1006/cviu.2000.0857).
    17. 17)
      • 17. Faugeras, O.D., Luong, Q.T., Maybank, S.J.: ‘Camera self-calibration: theory and experiments’. European Conf. Computer Vision, Santa Margherita, Italy, 1992, pp. 321334.
    18. 18)
      • 18. Hung, Y.-P., Shieh, S.-W.: ‘When should we consider lens distortion in camera calibration’. IAPR Workshop on Machine Vision Applications, Tokyo, 1990.
    19. 19)
      • 19. Faugeras, O.D., Toscani, G.: ‘The calibration problem for stereo’. Proc. Conf. on Computer Vision and Pattern Recognition, Miami Beach, Florida, 1986, pp. 1520.
    20. 20)
      • 20. Strat, T.M.: ‘Recovering the camera parameters from a transformation matrix’. Proc. of the DARPA IU Workshop, New Orleans, 1984, pp. 264271..
    21. 21)
      • 21. Sutherland, I.: ‘Three-dimensional data input by tablet’, Proc. IEEE, 1974, 62, (4), pp. 453461 (doi: 10.1109/PROC.1974.9449).
    22. 22)
      • 22. Horaud, R., Conio, B., Leboulleux, O.: ‘An analytic solution for the perspective 4-point problem’, Comput. Vis., Graph., Image Process., 1989, 47, pp. 3344 (doi: 10.1016/0734-189X(89)90052-2).
    23. 23)
      • 23. Holt, R.J., Netravali, A.N.: ‘Camera calibration problem: some new results’, CVGIP: Image Underst., 1991, 54, pp. 368383 (doi: 10.1016/1049-9660(91)90037-P).
    24. 24)
      • 24. CVOnline, University of Edinburgh. April 1997, April CVOnline. [Online].
    25. 25)
      • 25. Hartley, R.: ‘In defence of the eight-point algorithm’, IEEE Trans. Pattern Anal. Mach. Intell., 1997, 19, (6), pp. 580593 (doi: 10.1109/34.601246).
    26. 26)
      • 26. Bouguet, J.-Y.: Caltech Camera Calibration Toolbox for Matlab. April 2010 [Online].

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