Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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RANSAC-based Or thogonal Vanishing Point Estimation in the Equirectangular Images

  • Oh, Seon Ho (School of Computer Science and Engineering, College of IT Engineering, Kyungpook National University) ;
  • Jung, Soon Ki (School of Computer Science and Engineering, College of IT Engineering, Kyungpook National University)
  • Received : 2012.09.22
  • Accepted : 2012.11.03
  • Published : 2012.12.31
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Abstract

In this paper, we present an algorithm that quickly and effectively estimates orthogonal vanishing points in equirectangular images of urban environment. Our algorithm is based on the RANSAC (RANdom SAmple Consensus) algorithm and on the characteristics of the line segment in the spherical panorama image of the $360^{\circ}$ longitude and $180^{\circ}$ latitude field of view. These characteristics can be used to reduce the geometric ambiguity in the line segment classification as well as to improve the robustness of vanishing point estimation. The proposed algorithm is validated experimentally on a wide set of images. The results show that our algorithm provides excellent levels of accuracy for the vanishing point estimation as well as line segment classification.

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References

  1. K.J. Ban, J.C. Kim, E.K. Kon, and C.Y. Kim, "A Study of Generating Depth map for D Space Structure Recovery," Journal of Korea Multimedia Society, Vol. 13, No. 12, pp. 1855-1862, 2010.
  2. D.N. Kim and K.H. Jo, "Object Analysis on Outdoor Environment Using Multiple Features for Autonomous Navigation Robot," Journal of Korea Multimedia Society, Vol. 13, No. 5, pp. 651-662, 2010.
  3. S.C. Lee, S.K. Jung, and R. Nevatia, "Automatic Integration of Facade Textures into 3D Building Models with a Perspective Geometry Based Line Clustering," Computer Graphics Forum, Vol. 21, No. 3, pp. 511-519, 2002. https://doi.org/10.1111/1467-8659.00701
  4. E. Lutton, H. Maitre, and J. Lopez-Hrahe, "Contribution to the Determination of Vanishing Points using Hough Transform," IEEE Trans. Pattern Anal. Mach. Intell., Vol. 16, No. 4, pp. 430-438, 1994. https://doi.org/10.1109/34.277598
  5. L. Quan and R. Mohr, "Determining Perspective Structures using Hierarchical Hough Transform," Pattern Recognition Letters, Vol. 9, No. 4, pp. 279-286, 1989. https://doi.org/10.1016/0167-8655(89)90006-8
  6. S.T. Barnard. "Interpreting Perspective Images," Artif. Intell., Vol. 21, No. 4, pp. 435-462, 1983. https://doi.org/10.1016/S0004-3702(83)80021-6
  7. M. Antone and S. Teller, "Automatic Recovery of Relative Camera Rotations for Urban Scenes," Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Vol. 2, pp. 282-289, 2000.
  8. J.M. Coughlan and A.L. Yuille, "Manhattan World: Orientation Outlier Detection by Bayesian Inference," Neural Comput., Vol. 15, No. 5, pp. 1063-1088, 2003. https://doi.org/10.1162/089976603765202668
  9. P. Denis, J. Elder, and F. Estrada, "Efficient Edge-based Methods for Estimating Manhattan Frames in Urban Imagery," Proc. Euro. Conf. Comput. Vision, pp. 197-210, 2008.
  10. J. Kosecka and W. Zhang, "Video Compass," Proc. Euro. Conf. Comput. Vision, pp. 29-32, 2002.
  11. C. Rother, "A New Approach to Vanishing Point Detection in Architectural Environments," Image Vis. Comput., Vol. 20, No. 9-10, pp. 647-655, 2002. https://doi.org/10.1016/S0262-8856(02)00054-9
  12. M.A. Fischler and R.C. Bolles, "Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography," Comm. of the ACM, Vol. 24, No. 6, pp. 381-395, 1981. https://doi.org/10.1145/358669.358692
  13. D.G. Aguilera, J.G. Lahoz, and J.F. Codes, "A New Method for Vanishing Point Detection in 3D Reconstruction from a Single View," Proc. ISPRS Commission V, pp. 197-210, 2005.
  14. H. Wildenauer and M. Vincze, "Vanishing Point Detection in Complex Man-made Worlds," Proc. Int. Conf. Image Anal. Process., pp. 615-622, 2007.
  15. S. Sinha, D. Steedly, R. Szeliski, M. Agrawala, and M. Pollefeys, "Interactive 3D Architectural Modeling from Unordered Photo Collections," ACM Trans. Graphics, Vol. 27, No. 5, pp. 159:1-159:10, 2008.
  16. J.P. Tardif, "Non-iterative Approach for Fast and Accurate Vanishing Point Detection," IEEE International Conference on Computer Vision'09, pp. 1250-1257, 2009.
  17. H. Kang and K. Jo, "Analysis of Vanishing Curve and Points of Planar Objects from Single Panoramic Image," Int'l Forum on Strategic Technology, pp. 297-300, 2006.
  18. M. Bosse, R. Rikoski, J. Leonard, and S. Teller, "Vanishing Points and 3D Lines from Omnidirectional Video," The Visual Computer, Vol. 19, No. 6, pp. 417-430, 2003. https://doi.org/10.1007/s00371-003-0205-3
  19. S.H. Oh and S.K. Jung, "Vanishing Point Estimation in Equirectangular Images," Proc. Int'l Conf. Multimedia Information Technology and Applications, pp. 45-47. 2012.
  20. Flickr, Equirectangular, http://www.flickr.com/groups/equirectangular/, 2012.
  21. S.H. Oh and S.K. Jung, "A Great Circle arc Detector in Equirectangular Images," Proc. Int'l. Conf. Comput. Vision. Theory and Applications. pp. 346-351, 2012.
  22. M. Zuliani, "RANSAC Toolbox for Matlab," https://github.com/RANSAC/RANSAC-Toolbox, 2008.

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