Efficient Reconstruction of Complex 3-D Scenes from Incomplete RGB-D Data

  • Sergio A. Mota-Gutierrez
  • Jean-Bernard Hayet
  • Salvador Ruiz-Correa
  • Rogelio Hasimoto-Beltran
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8334)


In this paper we develop a new approach for reconstructing 3-D scenes from RGB-D data. We use a Markov random field to model appearance relations and geometric cues between different regions of a scene, as a means to provide robustness to noisy and incomplete data often generated by RGB-D devices. A parametric reconstruction of 3-D scenes that enable coherent physical interaction are computed, in near real time, with a standard computer that does not use specialized hardware.


Graphical Processing Unit Augmented Reality Image Segment Kinect Sensor Structure From Motion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Sergio A. Mota-Gutierrez
    • 1
  • Jean-Bernard Hayet
    • 1
  • Salvador Ruiz-Correa
    • 1
  • Rogelio Hasimoto-Beltran
    • 1
  1. 1.Computer Science DepartmentCenter for Research in MathematicsGuanajuatoMéxico

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