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Vehicle Detection Using Appearance and Shape Constrained Active Basis Model

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Neural Information Processing (ICONIP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9491))

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Abstract

In this paper, we propose an Appearance and Shape Constrained Active Basis Model (ASC-ABM) to detect vehicles in image. ASC-ABM effectively incorporates the appearance and shape prior of vehicles in the active basis model. Therefore, compared with the original ABM, it can effectively remove the false positives caused by the clutter background and traffic lines. Experiment results demonstrate the effectiveness of the proposed method.

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Author information

Authors and Affiliations

  1. Beijing Laboratory of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing, 100081, People’s Republic of China

    Sai Liu & Mingtao Pei

Authors
  1. Sai Liu
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  2. Mingtao Pei
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Corresponding author

Correspondence to Sai Liu .

Editor information

Editors and Affiliations

  1. University of Istanbul, Istanbul, Turkey

    Sabri Arik

  2. University at Qatar, Doha, Qatar

    Tingwen Huang

  3. Tunku Abdul Rahman University College, Kuala Lumpur, Malaysia

    Weng Kin Lai

  4. University of Science Technology, Wuhan, China

    Qingshan Liu

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Liu, S., Pei, M. (2015). Vehicle Detection Using Appearance and Shape Constrained Active Basis Model. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9491. Springer, Cham. https://doi.org/10.1007/978-3-319-26555-1_48

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  • DOI: https://doi.org/10.1007/978-3-319-26555-1_48

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26554-4

  • Online ISBN: 978-3-319-26555-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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