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Hyperspectral Face Databases for Facial Recognition Research

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Book cover Face Recognition Across the Imaging Spectrum

Abstract

Spectral imaging (SI) enables us to collect various spectral information at specific wavelengths by dividing the spectrum into multiple bands. As such, SI offers a means to overcome several major challenges specific to current face recognition systems. However, the practical usage of hyperspectral face recognition (HFR) has, to date, been limited due to database restrictions in the public domain for comparatively evaluating HFR. In this chapter, we review four publically available hyperspectral face databases (HFDs): CMU, PolyU-HSFD, IRIS-M, and Stanford databases toward providing information on the key points of each of the considered databases. In addition, a new large HFD , called IRIS-HFD-2014, is introduced. IRIS-HFD-2014 can serve as a benchmark for statistically evaluating the performance of current and future HFR algorithms and will be made publicly available.

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Notes

  1. 1.

    http://www.palmir250.com/ir250pro.htm.

  2. 2.

    http://www.subtechnique.com/sony/PDFs/xc-7573e.pdf.

  3. 3.

    http://www.neo.no/hyspex/.

  4. 4.

    http://scien.stanford.edu/index.php/s_scenefrommultispectral-m/.

  5. 5.

    http://xritephoto.com/ph_product_overview.aspx?id=1192.

  6. 6.

    http://www.spectralcameras.com/varispec.

  7. 7.

    http://www.ximea.com/en/usb3-vision-camera/xiq.

  8. 8.

    http://www.ledgroupbuy.com/lumia-5-1-100w-full-spectrum-5-channel-led/.

  9. 9.

    http://oceanoptics.com/product/usb2000-custom/.

  10. 10.

    http://xritephoto.com/ph_product_overview.aspx?ID=1234.

  11. 11.

    http://www.csse.uwa.edu.au/~ajmal/.

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Acknowledgement

We would like to thank all the participants in IRIS-HFD-2014. This publication was made possible by NPRP grant #4-1165-2-453 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

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Authors and Affiliations

  1. Department of Electrical Engineering and Computer Science, University of Tennessee, 37996-2250, Knoxville, TN, USA

    Woon Cho, Andreas Koschan & Mongi A. Abidi

Authors
  1. Woon Cho
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  2. Andreas Koschan
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  3. Mongi A. Abidi
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Correspondence to Woon Cho .

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Editors and Affiliations

  1. Multispectral Imagery Lab—MILab, LCSEE, West Virginia University, MORGANTOWN, West Virginia, USA

    Thirimachos Bourlai

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Cho, W., Koschan, A., Abidi, M.A. (2016). Hyperspectral Face Databases for Facial Recognition Research. In: Bourlai, T. (eds) Face Recognition Across the Imaging Spectrum. Springer, Cham. https://doi.org/10.1007/978-3-319-28501-6_3

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  • DOI: https://doi.org/10.1007/978-3-319-28501-6_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28499-6

  • Online ISBN: 978-3-319-28501-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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