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Adaptive Haar-Like Features for Head Pose Estimation

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Image Analysis and Recognition (ICIAR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8815))

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Abstract

This paper presents a work on head pose estimation. Here, face images are tagged with head pose information. To achieve head pose estimation, anatomic regions (eyes, nose and mouth) are extracted using a facial descriptor. Candidates for these regions are extracted from an energy map based on Haar-like features. Then, a multi-threshold analysis is applied to find the position and the size of each region. Region projections on vertical and horizontal axis enable to define a set of rules in order to estimate head pose.

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Author information

Authors and Affiliations

  1. LIPADE, Paris Descartes University, 45 rue des Saints-Pères, 75006, Paris, France

    Nam-Jun Pyun, Halima Sayah & Nicole Vincent

  2. Konbini, 20 rue du Faubourg du Temple, 75011, Paris, France

    Nam-Jun Pyun

Authors
  1. Nam-Jun Pyun
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  2. Halima Sayah
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  3. Nicole Vincent
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Corresponding author

Correspondence to Nam-Jun Pyun .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Porto, Porto, Portugal

    Aurélio Campilho

  2. Dept. of Electrical and Computer Eng., University of Waterloo, Waterloo, Ontario, Canada

    Mohamed Kamel

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© 2014 Springer International Publishing Switzerland

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Pyun, NJ., Sayah, H., Vincent, N. (2014). Adaptive Haar-Like Features for Head Pose Estimation. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8815. Springer, Cham. https://doi.org/10.1007/978-3-319-11755-3_11

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  • DOI: https://doi.org/10.1007/978-3-319-11755-3_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11754-6

  • Online ISBN: 978-3-319-11755-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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