Color Image Segmentation Based on an Iterative Graph Cut Algorithm Using Time-of-Flight Cameras

  • Markus Franke
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6835)


This work describes an approach to color image segmentation by supporting an iterative graph cut segmentation algorithm with depth data collected by time-of-flight (TOF) cameras. The graph cut algorithm uses an energy minimization approach to segment an image, taking account of both color and contrast information. The foreground and background color distributions of the images subject to segmentation are represented by Gaussian mixture models, which are optimized iteratively by parameter learning. These models are initialized by a preliminary segmentation created from depth data, automating the model initialization step, which otherwise relies on user input.


Gaussian Mixture Model Search Tree Segmentation Result Depth Image Depth Data 
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 2011

Authors and Affiliations

  • Markus Franke
    • 1
  1. 1.Multimedia Information Processing Group Department of Computer ScienceChristian Albrechts University of KielGermany

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