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In-attention State Monitoring for a Driver Based on Head Pose and Eye Blinking Detection Using One Class Support Vector Machine

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Neural Information Processing (ICONIP 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8835))

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Abstract

This paper proposes a model to detect inattention cognitive state of a driver during various driving situations. The proposed system predicts driver’s inattention state based on the analysis of eye blinking patterns and head pose direction. The study uses an infrared camera and several feature extraction stages such as modified census transform (MCT) to reduce the effect of light source change in real traffic environment. Also, we propose a new eye blinking detection using the difference between center and surround of Hough circle transform image. The local linear embedding (LLE) is used to extract real-time features of head movement. Finally, the driver’s cognitive states can be estimated by the one-class support vector machines (OCSVMs) using both eyes blinking patterns and head pose direction information. We implement a prototype of the proposed driver state monitoring (DSM) system. Experimental results show that the proposed system using OCSVM works well in real environment compared to the system that employs SVM.

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Author information

Authors and Affiliations

  1. School of Electronics Engineering, Kyungpook National University, 1370 Sankyuk-Dong, Puk-Gu, Taegu, 702-701, South Korea

    Hyunrae Jo & Minho Lee

Authors
  1. Hyunrae Jo
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  2. Minho Lee
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Faculty of Computer Science and Information Technology Building, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Chu Kiong Loo

  2. Department of Electronics and Communication Engineering, College of Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43009, Kajang, Selangor, Malaysia

    Keem Siah Yap

  3. School of Engineering and Information Technology, Murdoch University, South St., 6150, Murdoch, Western Australia, Australia

    Kok Wai Wong

  4. Department of Electrical and Electronics Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, 120-749, Seoul, South Korea

    Andrew Teoh

  5. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Ren’ai Road 111, SIP 215123, Suzhou, Jiangsu Province, China

    Kaizhu Huang

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© 2014 Springer International Publishing Switzerland

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Jo, H., Lee, M. (2014). In-attention State Monitoring for a Driver Based on Head Pose and Eye Blinking Detection Using One Class Support Vector Machine. In: Loo, C.K., Yap, K.S., Wong, K.W., Teoh, A., Huang, K. (eds) Neural Information Processing. ICONIP 2014. Lecture Notes in Computer Science, vol 8835. Springer, Cham. https://doi.org/10.1007/978-3-319-12640-1_14

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  • DOI: https://doi.org/10.1007/978-3-319-12640-1_14

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12639-5

  • Online ISBN: 978-3-319-12640-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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