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Extended GrabCut for 3D and RGB-D Point Clouds

  • Nizar K. Sallem
  • Michel Devy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8192)

Abstract

GrabCut is a renowned algorithm for image segmentation. It exploits iteratively the combinatorial minimization of energy function as introduced in graph-cut methods, to achieve background foreground classification with fewer user’s interaction. In this paper it is proposed to extend GrabCut to carry out segmentation on RGB-D point clouds, based both on appearance and geometrical criteria. It is shown that an hybrid GrabCut method combining RGB and D information, is more efficient than GrabCut based only on RGB or D images.

Keywords

segmentation graph-cut GrabCut RGB-D max-flow 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Nizar K. Sallem
    • 1
    • 2
  • Michel Devy
    • 1
    • 2
  1. 1.CNRS, LAASToulouseFrance
  2. 2.Université de Toulouse, LAASToulouseFrance

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