Multimodal Segmentation of Dense Depth Maps and Associated Color Information

  • Maciej Stefańczyk
  • Włodzimierz Kasprzak
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7594)


An integrated segmentation approach for color images and depth maps is proposed. The 3D pointclouds are characterized by normal vectors and then grouped into planar, concave or convex faces. The empty regions in the depth map are filled by segments of the associated color image. In the experimental part two types of depth maps are analysed: generated by the MS-Kinect sensor or by a stereo-pair of cameras.


depth map integrated image segmentation surface segmentation 3D point clouds 


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  1. 1.
    Surmann, H., Nüchter, A., Hertzberg, J.: An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments. Robotics and Autonomous Systems 45(3), 181–198 (2003)CrossRefGoogle Scholar
  2. 2.
    Konolige, K.: Projected texture stereo. In: 2010 IEEE International Conference on Robotics and Automation (ICRA), pp. 148–155. IEEE (2010)Google Scholar
  3. 3.
    Giles, J.: Inside the race to hack the Kinect. The New Scientist 208(2789), 22–23 (2010)CrossRefGoogle Scholar
  4. 4.
    Lange, R., Seitz, P.: Solid-state time-of-flight range camera. IEEE Journal of Quantum Electronics 37(3), 390–397 (2001)CrossRefGoogle Scholar
  5. 5.
    Dey, T., Li, G., Sun, J.: Normal estimation for point clouds: A comparison study for a Voronoi based method. In: Point-Based Graphics, Eurographics/IEEE VGTC Symposium Proceedings, pp. 39–46. IEEE (2005)Google Scholar
  6. 6.
    Miao, Y., Feng, J., Peng, Q.-S.: Curvature Estimation of Point-Sampled Surfaces and Its Applications. In: Gervasi, O., Gavrilova, M.L., Kumar, V., Laganá, A., Lee, H.P., Mun, Y., Taniar, D., Tan, C.J.K. (eds.) ICCSA 2005. LNCS, vol. 3482, pp. 1023–1032. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  7. 7.
    Kornuta, T., Stefańczyk, M.: DisCODe: component-oriented framework for sensory data processing (PL). Measurements, Automation and Robotics 16(7-8), 76–83 (2012)Google Scholar
  8. 8.
    Giordano, P., De Luca, A., Oriolo, G.: 3D structure identification from image moments. In: IEEE International Conference on Robotics and Automation, ICRA 2008, pp. 93–100. IEEE (2008)Google Scholar
  9. 9.
    Mahmoudi, M., Sapiro, G.: Three-dimensional point cloud recognition via distributions of geometric distances. Graphical Models 71(1), 22–31 (2009)CrossRefGoogle Scholar
  10. 10.
    Jaklic, A., Leonardis, A., Solina, F.: Segmentation and Recovery of Superquadrics. Computational imaging and vision, vol. 20. Kluwer, Dordrecht (2000)CrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Maciej Stefańczyk
    • 1
  • Włodzimierz Kasprzak
    • 1
  1. 1.Institute of Control and Computation Eng.Warsaw University of TechnologyWarsawPoland

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