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International Work-Conference on Artificial Neural Networks

IWANN 2015: Advances in Computational Intelligence pp 103–114Cite as

Automatic Eye Blink Detection Using Consumer Web Cameras

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9095))

Abstract

This research aims to advance blinking detection in the context of work activity. Rather than patients having to attend a clinic, blinking videos can be acquired in a work environment, and further automatically analyzed. Therefore, this paper presents a methodology to perform the automatic detection of eye blink using consumer videos acquired with low-cost web cameras. This methodology includes the detection of the face and eyes of the recorded person, and then it analyzes the low-level features of the eye region to create a quantitative vector. Finally, this vector is classified into one of the two categories considered —open and closed eyes— by using machine learning algorithms. The effectiveness of the proposed methodology was demonstrated since it provides unbiased results with classification errors under 5%.

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Author information

Authors and Affiliations

  1. Departamento de Computación, Universidade da Coruña, A Coruña, Spain

    Beatriz Remeseiro & Alba Fernández

  2. Centro de Física, Universidade do Minho, Guimarães, Portugal

    Madalena Lira

Authors
  1. Beatriz Remeseiro
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  2. Alba Fernández
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  3. Madalena Lira
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Corresponding author

Correspondence to Beatriz Remeseiro .

Editor information

Editors and Affiliations

  1. University of Granada, Granada, Spain

    Ignacio Rojas

  2. Department of Electronics Technology, University of Malaga, Malaga, Spain

    Gonzalo Joya

  3. Polytechnic University of Catalonia, Vilanova i la Geltrú, Spain

    Andreu Catala

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© 2015 Springer International Publishing Switzerland

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Remeseiro, B., Fernández, A., Lira, M. (2015). Automatic Eye Blink Detection Using Consumer Web Cameras. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2015. Lecture Notes in Computer Science(), vol 9095. Springer, Cham. https://doi.org/10.1007/978-3-319-19222-2_9

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  • DOI: https://doi.org/10.1007/978-3-319-19222-2_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19221-5

  • Online ISBN: 978-3-319-19222-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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