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International Conference on Neural Information Processing

ICONIP 2016: Neural Information Processing pp 673–681Cite as

Position Gradient and Plane Consistency Based Feature Extraction

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9948))

Abstract

Labeling scene objects is an essential task for many computer vision applications. However, differentiating scene objects with visual similarity is a very challenging task. To overcome this challenge, this paper proposes a position gradient and plane consistency based feature which is designed to distinguish visually similar objects and improve the overall labeling accuracy. Using the proposed feature we can differentiate objects with the same histogram of the gradient as well as we can differentiate horizontal and vertical objects. Integrating the proposed feature with low-level texture features and a neural network classifier, we achieve a superior performance (82 %) compared to state-of-the-art scene labeling methods on the Stanford background dataset.

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Author information

Authors and Affiliations

  1. Centre for Intelligent Systems, Central Queensland University, Brisbane, Australia

    Sujan Chowdhury, Brijesh Verma & Ligang Zhang

Authors
  1. Sujan Chowdhury
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  2. Brijesh Verma
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  3. Ligang Zhang
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Corresponding author

Correspondence to Sujan Chowdhury .

Editor information

Editors and Affiliations

  1. The University of Tokyo, Tokyo, Japan

    Akira Hirose

  2. Kobe University, Kobe, Japan

    Seiichi Ozawa

  3. Okinawa Institute of Science and Technology Graduate University, Onna, Japan

    Kenji Doya

  4. Nara Institute of Science and Technology, Ikoma, Japan

    Kazushi Ikeda

  5. Kyungpook National University, Daegu, Korea (Republic of)

    Minho Lee

  6. Chinese Academy of Sciences, Beijing, China

    Derong Liu

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© 2016 Springer International Publishing AG

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Chowdhury, S., Verma, B., Zhang, L. (2016). Position Gradient and Plane Consistency Based Feature Extraction. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science(), vol 9948. Springer, Cham. https://doi.org/10.1007/978-3-319-46672-9_75

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  • DOI: https://doi.org/10.1007/978-3-319-46672-9_75

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46671-2

  • Online ISBN: 978-3-319-46672-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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