OSA's Digital Library

Journal of the Optical Society of America A

Journal of the Optical Society of America A


  • Editor: Franco Gori
  • Vol. 31, Iss. 2 — Feb. 1, 2014
  • pp: 421–435

Wide-baseline stereo matching based on the line intersection context for real-time workspace modeling

Hyunwoo Kim, Sukhan Lee, and Yeonho Lee  »View Author Affiliations

JOSA A, Vol. 31, Issue 2, pp. 421-435 (2014)

View Full Text Article

Enhanced HTML    Acrobat PDF (2909 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



Line matching in widely separated views is challenging because of large perspective distortion and violation of the planarity assumption in local regions. We introduce a novel method of wide-baseline image matching based on the coplanar line intersections for poorly textured and/or nonplanar structured scenes. The local areas of the coplanar line pairs are normalized into canonical frames by rectifying the coplanar line pairs to be orthogonal. Then, the 3D interpretation of the intersection context of the coplanar line pairs helps to match the nonplanar local regions. Furthermore, for calibrated stereo cameras, we propose a matching criterion based on 3D planar homography to improve the matching accuracy while reconstructing most likely physically existing planar patches. Experimental results demonstrate the effectiveness of the proposed method for real-world scenes.

© 2014 Optical Society of America

OCIS Codes
(100.0100) Image processing : Image processing
(150.0150) Machine vision : Machine vision
(330.0330) Vision, color, and visual optics : Vision, color, and visual optics

ToC Category:
Vision, Color, and Visual Optics

Original Manuscript: May 16, 2013
Revised Manuscript: October 30, 2013
Manuscript Accepted: December 8, 2013
Published: January 31, 2014

Virtual Issues
Vol. 9, Iss. 4 Virtual Journal for Biomedical Optics

Hyunwoo Kim, Sukhan Lee, and Yeonho Lee, "Wide-baseline stereo matching based on the line intersection context for real-time workspace modeling," J. Opt. Soc. Am. A 31, 421-435 (2014)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. R. Datta, D. Joshi, J. Li, and J. Z. Wang, “Image retrieval: ideas, influences, and trends of the new age,” ACM Comput. Surv. 40, 5 (2008). [CrossRef]
  2. C. Baillard, C. Schmid, A. Zisserman, A. Fitzgibbon, and O. O. England, “Automatic line matching and 3D reconstruction of buildings from multiple views,” in ISPRS Conference on Automatic Extraction of GIS Objects from Digital Imagery (1999), pp. 69–80.
  3. B. Micusík and J. Kosecka, “Piecewise planar city 3D modeling from street view panoramic sequences,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Miami, Florida (2009), pp. 2906–2912.
  4. D. G. Lowe, “Distinctive image features from scale-invariant keypoints,” Int. J. Comput. Vis. 60, 91–110 (2004). [CrossRef]
  5. J. Ponce, M. Hebert, C. Schmid, and A. Zisserman, eds., Toward Category-Level Object Recognition, Lecture Notes in Computer Science (Springer, 2006), Vol. 4170.
  6. F. Zhou, H. B. L. Duh, and M. Billinghurst, “Trends in augmented reality tracking, interaction and display: a review of ten years of ISMAR,” in 7th IEEE/ACM International Symposium on Mixed and Augmented Reality (2008), pp. 193–202.
  7. J. Matas, O. Chum, U. Martin, and T. Pajdla, “Robust wide baseline stereo from maximally stable extremal regions,” in Proceedings of British Machine Vision Conference, London, UK (2002), pp. 384–393.
  8. T. Tuytelaars and L. Van Gool, “Matching widely separated views based on affine invariant regions,” Int. J. Comput. Vis. 59, 61–85 (2004). [CrossRef]
  9. K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F. Schaffalitzky, T. Kadir, and L. V. Gool, “A comparison of affine region detectors,” Int. J. Comput. Vis. 65, 43–72 (2005). [CrossRef]
  10. A. Vedaldi and S. Soatto, “Features for recognition: viewpoint invariance for non-planar scenes,” in Proceedings of the International Conference on Computer Vision (ICCV) (2005), pp. 1474–1481.
  11. E. Kim, G. Medioni, and S. Lee, “Planar patch based 3D environment modeling with stereo camera,” in 16th IEEE International Symposium on Robot and Human Interactive Communication, Jeju Island, Korea (2008), pp. 516–521.
  12. C. Schmid and A. Zisserman, “Automatic line matching across views,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (1997), pp. 666–671.
  13. T. Werner and A. Zisserman, “New techniques for automated architectural reconstruction from photographs,” in Proceedings of the 7th European Conference on Computer Vision. Part II, London, UK (Springer-Verlag, 2002), pp. 541–555.
  14. H. Bay, V. Ferrari, and L. Van Gool, “Wide-baseline stereo matching with line segments,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (2005), pp. 329–336.
  15. V. Ferrari, T. Tuytelaars, and L. V. Gool, “Wide-baseline muliple-view correspondences,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (2003), pp. 718–728.
  16. L. Wang, U. Neumann, and S. You, “Wide-baseline image matching using line signatures,” in Proceedings of the International Conference on Computer Vision (ICCV), Kyoto (2009).
  17. Z. Wang, F. Wu, and Z. Hu, “MSLD: a robust descriptor for line matching,” Pattern Recogn. 42, 941–953 (2009). [CrossRef]
  18. E. Vincent and R. Laganière, “Junction matching and fundamental matrix recovery in widely separated views,” in Proceedings of the British Machine Vision Conference, London, UK (2004), pp. 77–86.
  19. H. Bay, A. Ess, A. Neubeck, and L. V. Gool, “3D from line segments in two poorly-textured, uncalibrated images,” in Proceedings of the Third International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT), Chapel Hill, North Carolina (2006).
  20. B. Micusík, H. Wildenauer, and J. Kosecka, “Detection and matching of rectilinear structures,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Anchorage, Alaska (2008).
  21. H. Kim and S. Lee, “A novel line matching method based on intersection context,” in IEEE International Conference on Robotics and Automation (ICRA), Anchorage, Alaska (2010).
  22. H. Kim and S. Lee, “Simultaneous line matching and epipolar geometry estimation based on the intersection context of coplanar line pairs,” Pattern Recogn. Lett. 33, 1349–1363 (2012). [CrossRef]
  23. T. Werner, “Lmatch: Matlab toolbox for matching line segments accross multiple calibrated images,” http://cmp.felk.cvut.cz/~werner/software/lmatch/ (2007).
  24. P. Moreels and P. Perona, “Evaluation of features detectors and descriptors based on 3D objects,” Int. J. Comput. Vis. 73, 263–284 (2007). [CrossRef]
  25. F. Zhao, Q. Huang, and W. Gao, “Image matching by multiscale oriented corner correlation,” in Asian Conference on Computer Vision (2006), pp. 928–937.
  26. R. C. Gonzalez and R. E. Woods, Digital Image Processing, 3rd ed. (Prentice-Hall, 2006).
  27. R. I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, 2nd ed. (Cambridge University, 2004).
  28. M. I. A. Lourakis, S. V. Tzurbakis, A. A. Argyros, and S. C. Orphanoudakis, “Feature transfer and matching in disparate stereo views through the use of plane homographies,” IEEE Trans. Pattern Anal. Mach. Intell. 25, 271–276 (2003). [CrossRef]
  29. A. Vedaldi and B. Fulkerson, “VLFeat: an open and portable library of computer vision algorithms,” http://www.vlfeat.org/ (2008).
  30. H. Shao, T. Svoboda, and L. V. Gool, “Zubud-zurich buildings database for image based recognition,” (Swiss Federal Institute of Technology, 2003).

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited