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Graph Transduction Learning of Object Proposals for Video Object Segmentation

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Computer Vision -- ACCV 2014 (ACCV 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9006))

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Abstract

We propose an unsupervised video object segmentation algorithm that detects recurring objects and learns cohort object proposals over space-time. Our core contribution is a graph transduction process that learns object proposals densely over space-time, exploiting both appearance models learned from rudimentary detections of sparse object-like regions, and their intrinsic structures. Our approach exploits the fact that rudimentary detections of recurring objects in video, despite appearance variation and sporadity of detection, collectively describe the primary object. By learning a holistic model given a small set of object-like regions, we propagate this prior knowledge of the recurring primary object to the rest of the video to generate a diverse set of object proposals in all frames, incorporating both spatial and temporal cues. This set of rich descriptions underpins a robust object segmentation method against the changes in appearance, shape and occlusion in natural videos.

T. Wang and H. Wang—Indicates equal contribution.

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Notes

  1. 1.

    We used the publicly available source code from: http://vision.cs.utexas.edu/projects/keysegments/code/.

  2. 2.

    We used the publicly available source code from: http://dromston.com/projects/video_object_segmentation.php.

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Authors and Affiliations

  1. Nokia Technologies, Tampere, Finland

    Tinghuai Wang & Huiling Wang

Authors
  1. Tinghuai Wang
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  2. Huiling Wang
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Corresponding author

Correspondence to Tinghuai Wang .

Editor information

Editors and Affiliations

  1. Technische Universität München, Garching, Bayern, Germany

    Daniel Cremers

  2. University of Adelaide, Adelaide, South Australia, Australia

    Ian Reid

  3. Keio University, Yokohama, Kanagawa, Japan

    Hideo Saito

  4. University of California at Merced, Merced, California, USA

    Ming-Hsuan Yang

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Wang, T., Wang, H. (2015). Graph Transduction Learning of Object Proposals for Video Object Segmentation. In: Cremers, D., Reid, I., Saito, H., Yang, MH. (eds) Computer Vision -- ACCV 2014. ACCV 2014. Lecture Notes in Computer Science(), vol 9006. Springer, Cham. https://doi.org/10.1007/978-3-319-16817-3_36

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  • DOI: https://doi.org/10.1007/978-3-319-16817-3_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16816-6

  • Online ISBN: 978-3-319-16817-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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