Omnidirectional Vision for Indoor Spatial Layout Recovery

  • J. Omedes
  • G. López-Nicolás
  • J. J. Guerrero
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 193)


In this work, we study the problem of recovering the spatial layout of a scene from a collection of lines extracted from a single indoor image. Equivalent methods for conventional cameras have been proposed in the literature, but not much work has been done about this topic using omnidirectional vision, particulary powerful to obtain the spatial layout due to its wide field of view. As the geometry of omnidirectional and conventional images is different, most of the proposed methods for standard cameras do not work and new algorithms with specific considerations are required. We first propose a new method for vanishing points (VPs) estimation and line classification for omnidirectional images. Our main contribution is a new approach for spatial layout recovery based on these extracted lines and vanishing points, combined with a set of geometrical constraints, which allow us to detect floor-wall boundaries regardless of the number of walls. In our proposal, we first make a 4 walls room hypothesis and subsequently we expand this room in order to find the best fitting. We demonstrate how we can find the floor-wall boundary of the interior of a building, even when this boundary is partially occluded by objects and show several examples of these interpretations.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Coughlan, J.M., Yuille, A.L.: Manhattan world: Compass direction from a single image by bayesian inference. In: Int. Conf. on Computer Vision, pp. 941–947 (1999)Google Scholar
  2. 2.
    Lee, D., Hebert, M., Kanade, T.: Geometric reasoning for single image structure recovery. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 2136–2143 (June 2009)Google Scholar
  3. 3.
    Hedau, V., Hoiem, D., Forsyth, D.: Recovering the spatial layout of cluttered rooms. In: IEEE International Conference on Computer Vision, pp. 1849–1856 (2009)Google Scholar
  4. 4.
    Tsai, G., Xu, C., Liu, J., Kuipers, B.: Real-time indoor scene understanding using bayesian filtering with motion cues. In: ICCV, pp. 121–128 (2011)Google Scholar
  5. 5.
    Ozisik, N.D., López-Nicolás, G., Guerrero, J.J.: Scene structure recovery from a single omnidirectional image. In: ICCV Workshops, pp. 359–366 (2011)Google Scholar
  6. 6.
    Bazin, J.C., Kweon, I., Demonceaux, C., Vasseur, P.: A robust top-down approach for rotation estimation and vanishing points extraction by catadioptric vision in urban environment. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 346–353 (2008)Google Scholar
  7. 7.
    Bermudez, J., Puig, L., Guerrero, J.J.: Line extraction in central hyper-catadioptric systems. In: OMNIVIS (2010)Google Scholar
  8. 8.
    Geyer, C., Daniilidis, K.: A Unifying Theory for Central Panoramic Systems and Practical Implications. In: Vernon, D. (ed.) ECCV 2000, Part II. LNCS, vol. 1843, pp. 445–461. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  9. 9.
    Bermudez-Cameo, J., Puig, L., Guerrero, J.J.: Hypercatadioptric line images for 3d orientation and image rectification. Robotics and Autonomous Systems 60(6), 755–768 (2012)CrossRefGoogle Scholar
  10. 10.
    Barreto, J.: General central projection systems: Modeling, calibration and visual servoing. Ph.D. dissertation (2003)Google Scholar
  11. 11.
    Sturm, P., Gargallo, P.: Conic fitting using the geometric distance. In: Proceedings of the Asian Conference on Computer Vision, Tokyo, Japan, pp. 784–795 (2007)Google Scholar
  12. 12.
    Zivkovic, Z., Booij, O., Krose, B.: From images to rooms. Robotics and Autonomous Systems 55(5), 411–418 (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • J. Omedes
    • 1
  • G. López-Nicolás
    • 1
  • J. J. Guerrero
    • 1
  1. 1.Instituto de Investigación en Ingeniería de AragónUniversidad de ZaragozaZaragozaSpain

Personalised recommendations