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A Novel Context-Aware Topic Model for Category Discovery in Natural Scenes

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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

Automatic category discovery from images is a challenging problem in computer vision community especially from natural scene images due to the great variability in them. This paper proposes a novel context-aware topic model for category discovery in complex natural scenes. The proposed model constructs a generative probabilistic procedure from three-level features consisting of patch, region and the entire image by introducing latent topic variables to every patch and every region. Additionally, a new kind of scene context prior, namely, the spatial preference of categories, is also modeled using only a few parameters to reduce the ambiguity of categories in scene images. By regarding “topics” as “categories”, category discovery is thus converted to the inference of the proposed probabilistic model, which will further be addressed under a Gibbs-EM framework effectively. Experimental results on two benchmark datasets comprising MSRC-v2 and SIFT Flow show its effectiveness and the advantages comparing with other methods.

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Acknowledgement

The work described in this paper was supported by the Natural Science Foundation of China under Grant No. 61272218 and No. 61321491, the 973 Program of China under Grant No. 2010CB327903, and the Program for New Century Excellent Talents under NCET-11-0232.

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Authors and Affiliations

  1. National Key Lab for Novel Software Technology, Nanjing University, Nanjing, China

    Zehuan Yuan & Tong Lu

Authors
  1. Zehuan Yuan
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  2. Tong Lu
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Corresponding author

Correspondence to Tong Lu .

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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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Yuan, Z., Lu, T. (2015). A Novel Context-Aware Topic Model for Category Discovery in Natural Scenes. 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_11

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  • DOI: https://doi.org/10.1007/978-3-319-16817-3_11

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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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