Using vanishing points to estimate parameters of fisheye camera
Using vanishing points to estimate parameters of fisheye camera
- Author(s): Haijiang Zhu ; Xiaobo Xu ; Jinglin Zhou ; Xuejing Wang
- DOI: 10.1049/iet-cvi.2013.0013
For access to this article, please select a purchase option:
Buy article PDF
Buy Knowledge Pack
IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.
Thank you
Your recommendation has been sent to your librarian.
- Author(s): Haijiang Zhu 1 ; Xiaobo Xu 1 ; Jinglin Zhou 1 ; Xuejing Wang 1
-
-
View affiliations
-
Affiliations:
1:
College of Information & Technology, Beijing University of Chemical Technology, Beijing 100029, People's Republic of China
-
Affiliations:
1:
College of Information & Technology, Beijing University of Chemical Technology, Beijing 100029, People's Republic of China
- Source:
Volume 7, Issue 5,
October 2013,
p.
362 – 372
DOI: 10.1049/iet-cvi.2013.0013 , Print ISSN 1751-9632, Online ISSN 1751-9640
This study presents an approach for estimating the fisheye camera parameters using three vanishing points corresponding to three sets of mutually orthogonal parallel lines in one single image. The authors first derive three constraint equations on the elements of the rotation matrix in proportion to the coordinates of the vanishing points. From these constraints, the rotation matrix is calculated under the assumption of the image centre known. The experimental results with synthetic images and real fisheye images validate this method. In contrast to the existing methods, the authors method needs less image information and does not know the three-dimensional reference point coordinates.
Inspec keywords: matrix algebra; cameras; image processing; parameter estimation
Other keywords: synthetic images; single image; constraint equations; parameter estimation; rotation matrix; three-dimensional reference point coordinates; vanishing points; image information; fisheye camera; real fisheye images; mutually orthogonal parallel lines
Subjects: Algebra; Optical, image and video signal processing; Algebra; Computer vision and image processing techniques; Image sensors
References
-
-
1)
-
1. Caprile, B., Torre, V.: ‘Using vanishing points for camera calibration’, Int. J. Comput. Vis., 1990, 4, (2), pp. 127–139 (doi: 10.1007/BF00127813).
-
-
2)
-
2. Svedberg, D., Carlsson, S.: ‘Calibration, pose and novel views from single images of constrained scenes’, Pattern Recognit. Lett., 2000, 21, (13–14), pp. 1125–1133 (doi: 10.1016/S0167-8655(00)00073-8).
-
-
3)
-
3. Wilczkowiak, M., Sturm, P., Boyer, E.: ‘Using geometric constraints through parallelepipeds for calibration and 3D modeling’, Trans. Pattern Anal. Mach. Intell., 2005, 27, (2), pp. 194–207 (doi: 10.1109/TPAMI.2005.40).
-
-
4)
-
4. Hartley, R., Zisserman, A.: ‘Multiple view geometry in computer vision’ (Cambridge University press, 2003, 2nd edn.).
-
-
5)
-
5. Gallagher, A.C.: ‘Using vanishing points to correct camera rotation in images’. Proc. Second Canadian Conf. Computer and Robot Vision, May 2005.
-
-
6)
-
6. Avinash, N., Murali, S.: ‘Perspective geometry based single image camera calibration’, J. Math. Imaging Vis., 2008, 30, (3), pp. 221–230 (doi: 10.1007/s10851-007-0052-3).
-
-
7)
-
7. Mirzaei, F.M., Roumeliotis, S.: ‘Optimal estimation of vanishing points in a Manhattan world’. Proc. IEEE Int. Conf. Computer Vision, 2011, pp. 2454–2461.
-
-
8)
-
8. Homacek, M., Maierhofer, S.: ‘Extracting vanishing points across multiple views’. IEEE Conf. Computer Vision and Pattern Recognition, 2011, pp. 953–960.
-
-
9)
-
9. Babaee, K.V., Pourreza, H.R.: ‘Camera parameters estimation in soccer scenes on the basis of points at infinity’, IET Comput. Vis., 2012, 6, (2), pp. 133–139 (doi: 10.1049/iet-cvi.2010.0107).
-
-
10)
-
10. Nayar, S.: ‘Catadioptric omnidirectional camera’. IEEE Conf. Computer Vision and Pattern Recognition, 1997, pp. 482–488.
-
-
11)
-
11. Geyer, C., Daniilidis, K.: ‘Catadioptric camera calibration’, Int. J. Comput. Vis., 1999, pp. 398–404.
-
-
12)
-
12. Geyer, C., Daniilidis, K.: ‘Catadioptric projective geometry’, Int. J. Comput. Vis., 2001, 45, (3), pp. 223–243 (doi: 10.1023/A:1013610201135).
-
-
13)
-
13. Wu, Y., Hu, Z.: ‘Geometric invariants and applications under catadioptric camera model’. Proc. ICCV, 2005, vol. 1, pp. 1547–1554.
-
-
14)
-
14. Ying, X., Hu, Z.: ‘Can we consider central catadioptric cameras and fisheye cameras within a unified imaging model’ (ECCV, 2004) pp. 442–455.
-
-
15)
-
15. Scaramuzza, D., Martinelli, A., Siegwart, R.: ‘A flexible technique for accurate omnidirectional camera calibration and structure from motion’. Proc. IEEE Int. Conf. Computer Vision Systems, 2006.
-
-
16)
-
16. Mei, C., Rives, P.: ‘Single view point omnidirectional camera calibration from planar grids’. IEEE Int. Conf. Robotics and Automation, 2007, pp. 3945–3950.
-
-
17)
-
17. Chen, X., Yang, J., Waibel, A.: ‘Calibration of a hybrid camera network’. Proc. Ninth IEEE Int. Conf. Computer Vision, 2003, vol. 1, pp. 150–155.
-
-
18)
-
18. Bazin, J.C., Kweon, I.S., Demonceaux, C., Vasseur, P.: ‘Uav attitude estimation by vanishing points in catadioptric images’. IEEE Int. Conf. Robotics and Automation, 2008, pp. 2743–2749.
-
-
19)
-
19. Ho, T.H., Davis, C.C., Milner, S.D.: ‘Using geometric constraints for fisheye camera calibration’. Proc. IEEE OMNIVIS Workshop, 2005.
-
-
20)
-
20. Micusík, B., Pajdla, T.: ‘Structure from motion with wide circular field of view cameras’, IEEE Trans. Pattern Anal. Mach. Intell., 2006, 28, (7), pp. 1135–1149 (doi: 10.1109/TPAMI.2006.151).
-
-
21)
-
21. Kannala, J., Brandt, S.S.: ‘A generic camera model and calibration method for conventenal, wide-eye, and fish-eye lenses’, IEEE Trans. Pattern Anal. Mach. Intell., 2006, 28, (8), pp. 1335–1340 (doi: 10.1109/TPAMI.2006.153).
-
-
22)
-
22. Hughes, C., Denny, P., Glavin, M., Jones, E.: ‘Equidistant fish-eye calibration and rectification by vanishing point extraction’, IEEE Trans. Pattern Anal. Mach. Intell., 2010, 32, (12), pp. 2289–2296 (doi: 10.1109/TPAMI.2010.159).
-
-
23)
-
23. Liu, J.J., Phillips, C., Daniilidia, K.: ‘Video-based localization without 3D mapping for the visually impaired’. Proc. 2010 IEEE Computer Society Conf. Computer Vision and Pattern Recognition – Workshops, 2010, pp. 23–30.
-
-
24)
-
24. Hansen, P., Corke, P., Boles, W.: ‘Wide-angle visual feature matching for outdoor localization’, Int. J. Robot. Res., 2010, 29, (2–3), pp. 267–297 (doi: 10.1177/0278364909356484).
-
-
25)
-
25. Kruger, L., Wohler, C.: ‘Accurate chequerboard corner localisation for camera calibration’, Pattern Recognit. Lett., 2011, 32, (10), pp. 1428–1435 (doi: 10.1016/j.patrec.2011.04.002).
-
-
26)
-
26. Ryberg, A., Lennartson, B., Christiansson, A.K., Ericsson, M., Asplund, L.: ‘Analysis and evaluation of a general camera model’, Comput. Vis. Image Underst., 2011, 115, (11), pp. 1503–1515 (doi: 10.1016/j.cviu.2011.06.009).
-
-
27)
-
27. Li, W., Li, Y.F.: ‘Single-camera panoramic stereo imaging system with a fisheye lens and a convex mirror’, Opt. Express, 2011, 19, (7), pp. 5855–5867 (doi: 10.1364/OE.19.005855).
-
-
28)
-
28. Li, S., Hai, Y.: ‘Easy calibration of a blind-spot-free fisheye camera system using a scene of a parking space’, IEEE Trans. Intell. Transp. Syst., 2011, 12, (1), pp. 232–242 (doi: 10.1109/TITS.2010.2085435).
-
-
29)
-
29. Zhu, H., Yang, P., Li, S.: Estimating fisheye camera parameters from homography. Science China: Information Science, 2012, 55, (9), pp. 2119–2127.
-
-
30)
-
30. Goldreich, O.: ‘Computational complexity: a conceptual perspective’ (Cambridge University Press, 2010), available at http://www.en.wikipedia.org/wiki/Time_complexity.
-
-
1)

Related content
