Advertisement

Indoor Calibration Using Segment Chains

  • Jamil Draréni
  • Renaud Keriven
  • Renaud Marlet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6835)

Abstract

In this paper, we present a new method for line segments matching for indoor reconstruction. Instead of matching individual segments via a descriptor like most methods do, we match segment chains that have a distinctive topology using a dynamic programing formulation. Our method relies solely on the geometric layout of the segment chain and not on photometric or color profiles. Our tests showed that the presented method is robust and manages to produce calibration information even under a drastic change of viewpoint.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bay, H., Ferrari, V., Van Gool, L.: Wide-baseline stereo matching with line segments. In: CVPR 2005: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), vol. 1, pp. 329–336. IEEE Computer Society Press, Washington, DC (2005)Google Scholar
  2. 2.
    Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8, 679–698 (1986)CrossRefGoogle Scholar
  3. 3.
    Deriche, R., Faugeras, O.D.: Tracking line segments. In: Faugeras, O. (ed.) ECCV 1990. LNCS, vol. 427, pp. 259–268. Springer, Heidelberg (1990)CrossRefGoogle Scholar
  4. 4.
    Dragon, R., Shoaib, M., Rosenhahn, B., Ostermann, J.: NF-features – no-feature-features for representing non-textured regions. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6312, pp. 128–141. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  5. 5.
    Fan, B., Wu, F., Hu, Z.: Line matching leveraged by point correspondences. In: CVPR, pp. 390–397. IEEE, Los Alamitos (2010)Google Scholar
  6. 6.
    Grompone von Gioi, R., Jakubowicz, J., Morel, J.-M., Randall, G.: LSD: A fast line segment detector with a false detection control. IEEE Trans. Pattern Anal. Mach. Intell. 32(4), 722–732 (2010)CrossRefGoogle Scholar
  7. 7.
    Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2004) ISBN: 0521540518zbMATHCrossRefGoogle Scholar
  8. 8.
    Lindeberg, T.: Scale-Space Theory in Computer Vision. Kluwer Academic Publishers, Norwell (1994)Google Scholar
  9. 9.
    Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60(2), 91 (2004)CrossRefGoogle Scholar
  10. 10.
    Schmid, C., Zisserman, A.: Automatic line matching across views. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 666–671 (1997)Google Scholar
  11. 11.
    Wang, L., Neumann, U., You, S.: Wide-baseline image matching using line signatures. In: Proc. International Conference on Computer Vision. IEEE, Los Alamitos (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jamil Draréni
    • 1
  • Renaud Keriven
    • 1
  • Renaud Marlet
    • 1
  1. 1.IMAGINE, LIGMUniversité Paris-EstFrance

Personalised recommendations