access icon free Calibration of multiple fish-eye cameras using a wand

Fish-eye cameras are becoming increasingly popular in computer vision, but their use for three-dimensional measurement is limited partly because of the lack of an accurate, efficient and user-friendly calibration procedure. For such a purpose, the authors propose a method to calibrate the intrinsic and extrinsic parameters (including radial distortion parameters) of two/multiple fish-eye cameras simultaneously by using a wand under general motions. Thanks to the generic camera model used, the proposed calibration method is also suitable for two/multiple conventional cameras and mixed cameras (e.g. two conventional cameras and a fish-eye camera). Simulation and real experiments demonstrate the effectiveness of the proposed method. Moreover, the authors develop the camera calibration toolbox, which is available online.

Inspec keywords: computer vision; cameras; calibration

Other keywords: radial distortion parameters; three-dimensional measurement; fish-eye cameras; computer vision

Subjects: Optical, image and video signal processing; Computer vision and image processing techniques; Measurement standards and calibration; Image sensors

References

    1. 1)
      • 17. ‘Vicon Real-time motion capture system’, http://www.vicon.com/System/Calibration, accessedJune 2014.
    2. 2)
    3. 3)
      • 12. Feng, W., Röning, J., Kannala, J., Zong, X., Zhang, B.: ‘A general model and calibration method for spherical stereoscopic vision’. Proc. of the SPIE 8301, Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques, Burlingame, USA, 2012, p. 830107.
    4. 4)
    5. 5)
      • 4. Yamaguchi, J.: ‘Three dimensional measurement using fisheye stereo vision’, in Bhatti, A. (Ed.): ‘Advances in theory and applications of stereo vision’ (InTech, 2011), pp. 151164.
    6. 6)
    7. 7)
      • 26. Zheng, Y., Kuang, Y., Sugimoto, S., Åström, K., Okutomi, M.: ‘Revisiting the pnp problem: a fast, general and optimal solution’. Proc. of the IEEE Int. Conf. on Computer Vision, Sydney, Australia, 2013, pp. 23442351.
    8. 8)
      • 5. Havlena, M., Pajdla, T., Cornelis, K.: ‘Structure from omnidirectional stereo rig motion for city modeling’. Proc. of the Int. Conf. on Computer Vision Theory and Applications, Funchal, Portugal, 2008, pp. 407414.
    9. 9)
    10. 10)
    11. 11)
      • 9. Du, B., Zhu, H.: ‘Estimating fisheye camera parameters using one single image of 3D pattern’. Proc. of the Int. Conf. on Electric Information and Control Engineering, Wuhan, China, 2011, pp. 367370.
    12. 12)
      • 25. Chen, J.: ‘Dijkstra's shortest path algorithm’, Formalized Math., 2003, 11, (3), pp. 237247.
    13. 13)
    14. 14)
      • 20. Geyer, C., Daniilidis, K.: ‘A unifying theory for central panoramic systems and practical implications’. Proc. of the European Conf. on Computer Vision, Dublin, Ireland, 2000, pp. 445461.
    15. 15)
    16. 16)
      • 19. Kurillo, G., Li, Z., Bajcsy, R.: ‘Wide-area external multi-camera calibration using vision graphs and virtual calibration object’. Proc. of Second ACM/IEEE Int. Conf. on Distributed Smart Cameras, Stanford, USA, 2008, pp. 19.
    17. 17)
    18. 18)
    19. 19)
      • 11. Mei, C., Rives, P.: ‘Single view point omnidirectional camera calibration from planar grids’. Proc. of the IEEE Int. Conf. on Robotics and Automation, Roma, Italy, 2007, pp. 39453950.
    20. 20)
      • 28. Geiger, A., Moosmann, F., Car, Ö., Schuster, B.: ‘Automatic camera and range sensor calibration using a single shot’. Proc. of the Int. Conf. on Robotics and Automation, Saint Paul, USA, 2012, pp. 39363943.
    21. 21)
      • 18. Hartley, R., Zisserman, A.: ‘Multiple view geometry in computer vision’ (Cambridge University Press, 2004, 2nd edn.).
    22. 22)
      • 24. Lourakis, M.: ‘Sparse non-linear least squares optimization for geometric vision’. Proc. of the European Conf. on Computer Vision, Crete, Greece, 2010, pp. 4356.
    23. 23)
      • 27. Bouguet, J-Y.: ‘Camera calibration toolbox for matlab’, http://www.vision.caltech.edu/bouguetj/calib_doc/, accessed June 2014.
    24. 24)
      • 22. Svoboda, T., Pajdla, T., Hlaváč, V.: ‘Motion estimation using central panoramic cameras’. Proc. of the IEEE Conf. on Intelligent Vehicles, Stuttgart, Germany, 1998, pp. 335340.
    25. 25)
    26. 26)
    27. 27)
    28. 28)
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cvi.2014.0181
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