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Using a Robotic Arm for Measuring BRDFs

  • Rasmus Ahrenkiel Lyngby
  • Jannik Boll Matthiassen
  • Jeppe Revall FrisvadEmail author
  • Anders Bjorholm Dahl
  • Henrik Aanæs
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11482)

Abstract

The measurement of a bidirectional reflectance distribution function (BRDF) requires a purpose-built instrument. We ease this requirement by presenting a relative method for measuring a BRDF using a multipurpose robotic arm. Our focus is on the alignment of the system to perform accurate camera positioning and orientation. We use a six degrees of freedom robotic arm to move a camera on a hemisphere surrounding a flat material sample. Point-like light sources, fixed on a quarter circle arc, sequentially illuminate the sample from different directions. The resulting images are used to reconstruct the material BRDF. We limit ourselves to tristimulus (RGB) isotropic BRDF acquisition.

Keywords

Robot arm BRDF Camera pose estimation 

References

  1. 1.
    Baribeau, R., Neil, W.S., Côté, É.: Development of a robot-based gonioreflectometer for spectral BRDF measurement. J. Mod. Opt. 56(13), 1497–1503 (2009)CrossRefGoogle Scholar
  2. 2.
    Boby, R.A., Saha, S.K.: Single image based camera calibration and pose estimation of the end-effector of a robot. In: IEEE International Conference on Robotics and Automation, ICRA 2016, pp. 2435–2440 (2016)Google Scholar
  3. 3.
    Erb, W.: Computer-controlled gonioreflectometer for the measurement of spectral reflection characteristics. Appl. Opt. 19(22), 3789–3794 (1980)CrossRefGoogle Scholar
  4. 4.
    Höpe, A., Atamas, T., Hünerhoff, D., Teichert, S., Hauer, K.O.: ARGon\(^3\): 3D appearance robot-based gonioreflectometer at PTB. Rev. Sci. Instrum. 83(4), 045102 (2012)CrossRefGoogle Scholar
  5. 5.
    Hünerhoff, D., Grusemann, U., Höpe, A.: New robot-based gonioreflectometer for measuring spectral diffuse reflection. Metrologia 43(2), S11 (2006)CrossRefGoogle Scholar
  6. 6.
    Li, H., Foo, S.C., Torrance, K.E., Westin, S.H.: Automated three-axis gonioreflectometer for computer graphics applications. Opt. Eng. 45(4), 043605 (2006)CrossRefGoogle Scholar
  7. 7.
    Liang, R., Mao, J.: Hand-eye calibration with a new linear decomposition algorithm. J. Zhejiang Univ. Sci. A 9(10), 1363–1368 (2008)CrossRefGoogle Scholar
  8. 8.
    Martínez, M.L., Hartmann, T.: Multispectral gonioreflectometer facility for directional reflectance measurements and its use on materials and paints. In: Target and Background Signatures IV. Proceedings of SPIE, vol. 10794, p. 107940V (2018)Google Scholar
  9. 9.
    Matusik, W., Pfister, H., Brand, M., McMillan, L.: A data-driven reflectance model. ACM Trans. Graph. 22(3), 759–769 (2003). (SIGGRAPH 2003)CrossRefGoogle Scholar
  10. 10.
    Meng, Y., Zhuang, H.: Autonomous robot calibration using vision technology. Robot. Comput. Integr. Manuf. 23(4), 436–446 (2007)CrossRefGoogle Scholar
  11. 11.
    Nicodemus, F.E., Richmond, J.C., Hsia, J.J., Ginsberg, I.W., Limperis, T.: Geometrical considerations and nomenclature for reflectance. Technical report NBS Monograph 160, National Bureau of Standards (US), October 1977Google Scholar
  12. 12.
    Nielsen, J.B., et al.: Quality assurance based on descriptive and parsimonious appearance models. In: Material Appearance Modeling, MAM 2015, pp. 21–24 (2015)Google Scholar
  13. 13.
    Nielsen, J.B., Jensen, H., Ramamoorthi, R.: On optimal, minimal BRDF sampling for reflectance acquisition. ACM Trans. Graph. 34(6), 186:1–186:11 (2015). (SIGGRAPH Asia 2015)CrossRefGoogle Scholar
  14. 14.
    Nocedal, J., Wright, S.J.: Numerical Optimization, 2nd edn. Springer, Heidelberg (2006).  https://doi.org/10.1007/978-0-387-40065-5CrossRefzbMATHGoogle Scholar
  15. 15.
    Obein, G., Audenaert, J., Ged, G., Leloup, F.B.: Metrological issues related to BRDF measurements around the specular direction in the particular case of glossy surfaces. In: Measuring, Modeling, and Reproducing Material Appearance 2015. Proceedings of SPIE, vol. 9398, p. 93980D (2015)Google Scholar
  16. 16.
    Rabal, A.M., et al.: Automatic gonio-spectrophotometer for the absolute measurement of the spectral BRDF at in- and out-of-plane and retroreflection geometries. Metrologia 49(3), 213–223 (2012)CrossRefGoogle Scholar
  17. 17.
    Rusinkiewicz, S.: A new change of variables for efficient BRDF representation. In: Drettakis, G., Max, N. (eds.) Rendering Techniques ’98 (EGWR 1998), pp. 11–22. Springer, Heidelberg (1998).  https://doi.org/10.1007/978-3-7091-6453-2_2CrossRefGoogle Scholar
  18. 18.
    Stets, J.D., et al.: Scene reassembly after multimodal digitization and pipeline evaluation using photorealistic rendering. Appl. Opt. 56(27), 7679–7690 (2017)CrossRefGoogle Scholar
  19. 19.
    Wilson, W.J., Hulls, C.C.W., Bell, G.S.: Relative end-effector control using cartesian position based visual servoing. IEEE Trans. Robot. Autom. 12(5), 684–696 (1996)CrossRefGoogle Scholar
  20. 20.
    Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Rasmus Ahrenkiel Lyngby
    • 1
  • Jannik Boll Matthiassen
    • 1
  • Jeppe Revall Frisvad
    • 1
    Email author
  • Anders Bjorholm Dahl
    • 1
  • Henrik Aanæs
    • 1
  1. 1.Technical University of DenmarkKongens LyngbyDenmark

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