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Asian Conference on Computer Vision

ACCV 2014: Computer Vision – ACCV 2014 pp 335–350Cite as

Color Photometric Stereo Using a Rainbow Light for Non-Lambertian Multicolored Surfaces

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9003))

Abstract

This paper presents a novel approach for recovering the shape of non-Lambertian, multicolored objects using two input images. We show that a ring light source with complementary colored lights has the potential to be effectively utilized for this purpose. Under this lighting, the brightness of an object surface varies with respect to different reflections. Therefore, analyzing how brightness is modulated by illumination color gives us distinct cues to recover shape. Moreover, the use of complementary colored illumination enables the color photometric stereo to be applicable to multicolored surfaces. Here, we propose a color correction method based on the addition principle of complementary colors to remove the effect of illumination from the observed color. This allows the inclusion of surfaces with any number of chromaticities. Therefore, our method offers significant advantages over previous methods, which often assume constant object albedo and Lambertian reflectance. To the best of our knowledge, this is the first attempt to employ complementary colors on a ring light source to compute shape while considering both non-Lambertian reflection and spatially varying albedo. To show the efficacy of our method, we present results on synthetic and real world images and compare against photometric stereo methods elsewhere in the literature.

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Notes

  1. 1.

    This follows Newton’s geometrical weighting [28], which states that the additive mixture of any number of colors is determined as the weighted average of the positions of the original colors on the hue-saturation plane.

  2. 2.

    We note that in practice, \((P_i(\lambda )+\bar{P}_i(\lambda ))\) do not always perfectly sum to 1 at each wavelength. Despite this, since we ultimately examine RGB values in our method and not individual wavelengths, we found the amount of error introduced did not adversely affect our algorithm.

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Acknowledgement

This research was supported in part by the Ministry of Education, Science, Sports and Culture Grant-in-Aid for Scientific Research on Innovative Areas.

Author information

Authors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, USA

    Sejuti Rahman

  2. Saitama University, Saitama, Japan

    Antony Lam

  3. National Institute of Informatics, Tokyo, Japan

    Imari Sato

  4. National ICT Australia (NICTA), Canberra, Australia

    Antonio Robles-Kelly

Authors
  1. Sejuti Rahman
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  2. Antony Lam
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  3. Imari Sato
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  4. Antonio Robles-Kelly
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Corresponding author

Correspondence to Sejuti Rahman .

Editor information

Editors and Affiliations

  1. Technische Universität München, Garching, Bayern, Germany

    Daniel Cremers

  2. University of Adelaide, Adelaide, South Australia, Australia

    Ian Reid

  3. Keio University, Yokohama, Kanagawa, Japan

    Hideo Saito

  4. University of California at Merced, Merced, California, USA

    Ming-Hsuan Yang

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Rahman, S., Lam, A., Sato, I., Robles-Kelly, A. (2015). Color Photometric Stereo Using a Rainbow Light for Non-Lambertian Multicolored Surfaces. In: Cremers, D., Reid, I., Saito, H., Yang, MH. (eds) Computer Vision – ACCV 2014. ACCV 2014. Lecture Notes in Computer Science(), vol 9003. Springer, Cham. https://doi.org/10.1007/978-3-319-16865-4_22

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  • DOI: https://doi.org/10.1007/978-3-319-16865-4_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16864-7

  • Online ISBN: 978-3-319-16865-4

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