Background Cut

  • Jian Sun
  • Weiwei Zhang
  • Xiaoou Tang
  • Heung-Yeung Shum
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3952)


In this paper, we introduce background cut, a high quality and real-time foreground layer extraction algorithm. From a single video sequence with a moving foreground object and stationary background, our algorithm combines background subtraction, color and contrast cues to extract a foreground layer accurately and efficiently. The key idea in background cut is background contrast attenuation, which adaptively attenuates the contrasts in the background while preserving the contrasts across foreground/background boundaries. Our algorithm builds upon a key observation that the contrast (or more precisely, color image gradient) in the background is dissimilar to the contrast across foreground/background boundaries in most cases. Using background cut, the layer extraction errors caused by background clutter can be substantially reduced. Moreover, we present an adaptive mixture model of global and per-pixel background colors to improve the robustness of our system under various background changes. Experimental results of high quality composite video demonstrate the effectiveness of our background cut algorithm.


Segmentation Result Background Image Color Model Foreground Object Segmentation Boundary 
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 2006

Authors and Affiliations

  • Jian Sun
    • 1
  • Weiwei Zhang
    • 1
  • Xiaoou Tang
    • 1
  • Heung-Yeung Shum
    • 1
  1. 1.Microsoft Research AsiaBeijingP.R. China

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