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Video Object Segmentation Based on Superpixel Trajectories

  • Mohamed A. Abdelwahab
  • Moataz M. Abdelwahab
  • Hideaki Uchiyama
  • Atsushi Shimada
  • Rin-ichiro Taniguchi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9730)

Abstract

In this paper, a video object segmentation method utilizing the motion of superpixel centroids is proposed. Our method achieves the same advantages of methods based on clustering point trajectories, furthermore obtaining dense clustering labels from sparse ones becomes very easy. Simply for each superpixel the label of its centroid is propagated to all its entire pixels. In addition to the motion of superpixel centroids, histogram of oriented optical flow, HOOF, extracted from superpixels is used as a second feature. After segmenting each object, we distinguish between foreground objects and the background utilizing the obtained clustering results.

Keywords

Superpixel trajectory Object segmentation Affinity 

Notes

Acknowledgments

The authors would like to thank Egyptian Ministry of Higher Education (MoHE) and Egypt-Japan University of Science and Technology (E-JUST) for their support.

References

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Mohamed A. Abdelwahab
    • 1
    • 2
  • Moataz M. Abdelwahab
    • 1
  • Hideaki Uchiyama
    • 2
  • Atsushi Shimada
    • 2
  • Rin-ichiro Taniguchi
    • 2
  1. 1.Egypt Japan University of Science and TechnologyAlexandriaEgypt
  2. 2.Kyushu UniversityFukuokaJapan

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