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Vehicle Classification from Traffic Surveillance Videos at a Finer Granularity

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Advances in Multimedia Modeling (MMM 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4351))

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Abstract

This paper explores the computer vision based vehicle classification problem at a fine granularity. A framework is presented which incorporates various aspects of an Intelligent Transportation System towards vehicle classification. Given a traffic video sequence, the proposed framework first segments individual vehicles. Then vehicle segments are processed so that all vehicles are along the same direction and measured at the same scale. A filtering algorithm is applied to smooth the vehicle segment image. After these three steps of preprocessing, an ICA based algorithms is implemented to identify the features of each vehicle type. One-class SVM is used to categorize each vehicle into a certain class. Experimental results show the effectiveness of the framework.

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Author information

Authors and Affiliations

  1. Department of Computer and Information Sciences, University of Alabama at Birmingham, Birmingham, AL, 35294, USA

    Xin Chen & Chengcui Zhang

Authors
  1. Xin Chen
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  2. Chengcui Zhang
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Editor information

Editors and Affiliations

  1. School of Computer Engineering, Nanyang Technological University, Block N4, Nanyang Avenue, 639798, Singapore

    Tat-Jen Cham  & Deepu Rajan  & 

  2. School of Computer Engineering, Nanyang Technological University, 639798, Singapore

    Jianfei Cai

  3. IBM T.J. Watson Research Center, Yorktown Heights, P.O. Box 704, 10598, New York, USA

    Chitra Dorai

  4. National University of Singapore, 3 Science Dr, 117543, Singapore

    Tat-Seng Chua

  5. Center for Multimedia and Network Technology, School of Computer Enginnering, Nanyang Technological University, 639798, Singapore

    Liang-Tien Chia

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© 2006 Springer-Verlag Berlin Heidelberg

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Chen, X., Zhang, C. (2006). Vehicle Classification from Traffic Surveillance Videos at a Finer Granularity. In: Cham, TJ., Cai, J., Dorai, C., Rajan, D., Chua, TS., Chia, LT. (eds) Advances in Multimedia Modeling. MMM 2007. Lecture Notes in Computer Science, vol 4351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69423-6_75

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  • DOI: https://doi.org/10.1007/978-3-540-69423-6_75

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69421-2

  • Online ISBN: 978-3-540-69423-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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