Short-term motion-based object segmentation

  • Authors:
  • Marina Georgia Arvanitidou;Michael Tok;Andreas Krutz;Thomas Sikora

  • Affiliations:
  • Communication Systems Group, Technische Universität Berlin, Germany;Communication Systems Group, Technische Universität Berlin, Germany;Communication Systems Group, Technische Universität Berlin, Germany;Communication Systems Group, Technische Universität Berlin, Germany

  • Venue:
  • ICME '11 Proceedings of the 2011 IEEE International Conference on Multimedia and Expo
  • Year:
  • 2011

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Abstract

Motion-based segmentation approaches employ either longterm motion information, which is computationally demanding, or suffer from lack of accuracy when employing short-term information. We present an automatic motion-based object segmentation algorithm for video sequences with moving camera, employing short-term motion information solely. For every frame, two error frames are generated using motion compensation. They are combined and a thresholding segmentation algorithm is applied. Recent advances in the field of global motion estimation enable outlier elimination in the background area, and thus a more precise definition of the foreground is achieved. We propose a simple and effective error frame generation and consider spatial error localization. Thus, we achieve improved performance compared with a previously proposed short-term motion-based method and provide subjective as well as objective evaluation.