Abstract
In this paper, we propose a system that can measure the spatially-varying reflectance of real materials. Our system uses two handheld cameras, a small LED light, a turning table, and a chessboard with markers. The two cameras are used as a view and light cameras respectively to acquire incoming and outgoing light directions simultaneously, and the brightness at each position on the target material. The reflectance is approximated by using the Ward BRDF (Bidirectional Reflectance Distribution Function) model. The normal directions and all model parameters at each position on the material are estimated by non-linear optimization. As the result of experiment, the normal directions for all spatial points were properly estimated, and the correct colors of rendered materials were reproduced. Also, highlight changes on the surfaces were observed when we moved the light source or the rendered materials. It was confirmed that our system was easy to use and was able to measure the spatially-varying reflectance of real materials.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aittala, M., Weyrich, T., Lehtinen, J.: Practical SVBRDF capture in the frequency domain. ACM Trans. Graph. 32(4) (2013). https://doi.org/10.1145/2461912.2461978
Aittala, M., Weyrich, T., Lehtinen, J.: Two-shot SVBRDF capture for stationary materials. ACM Trans. Graph. 34(4) (2015). https://doi.org/10.1145/2766967
Baribeau, R., Neil, W.S., Côté, E.: Development of a robot-based gonioreflectometer for spectral BRDF measurement. J. Mod. Opt. 56(13), 1497–1503 (2009). https://doi.org/10.1080/09500340903045702
Dana, K.J., van Ginneken, B., Nayar, S.K., Koenderink, J.J.: Reflectance and texture of real-world surfaces. ACM Trans. Graph. 18(1), 1–34 (1999). https://doi.org/10.1145/300776.300778
Dana, K.J., Wang, J.: Device for convenient measurement of spatially varying bidirectional reflectance. J. Opt. Soc. Am. A 21(1), 1–12 (2004). https://doi.org/10.1364/JOSAA.21.000001. http://josaa.osa.org/abstract.cfm?URI=josaa-21-1-1
Dong, Y., et al.: Manifold bootstrapping for SVBRDF capture. ACM Trans. Graph. 29(4) (2010). https://doi.org/10.1145/1778765.1778835
Fichet, A., Sato, I., Holzschuch, N.: Capturing spatially varying anisotropic reflectance parameters using Fourier analysis. In: Proceedings of the 42nd Graphics Interface Conference, GI 2016, pp. 65–73. Canadian Human-Computer Communications Society, School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada (2016). https://doi.org/10.20380/GI2016.09
Filip, J., Vávra, R., Krupička, M.: Rapid material appearance acquisition using consumer hardware. Sensors (Basel, Switzerland) 14(10), 19785–19805 (2014). https://doi.org/10.3390/s141019785. https://pubmed.ncbi.nlm.nih.gov/25340451
Foo, S.C.: A gonioreflectometer for measuring the bidirectional reflectance of material for use in illumination computation (1997)
Gardner, A., Tchou, C., Hawkins, T., Debevec, P.: Linear light source reflectometry. ACM Trans. Graph. 22(3), 749–758 (2003). https://doi.org/10.1145/882262.882342
Garrido-Jurado, S., Muñoz Salinas, R., Madrid-Cuevas, F., Marín-Jiménez, M.: Automatic generation and detection of highly reliable fiducial markers under occlusion. Pattern Recogn. 47(6), 2280–2292 (2014). https://doi.org/10.1016/j.patcog.2014.01.005
Li, B., Feng, J., Zhou, B.: A SVBRDF modeling pipeline using pixel clustering (2019)
Lyngby, R.A., Matthiassen, J.B., Frisvad, J.R., Dahl, A.B., Aanæs, H.: Using a robotic arm for measuring BRDFs. In: Felsberg, M., Forssén, P.-E., Sintorn, I.-M., Unger, J. (eds.) SCIA 2019. LNCS, vol. 11482, pp. 184–196. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-20205-7_16
Mcallister, D.K., Lastra, A.: A generalized surface appearance representation for computer graphics. Ph.D. thesis (2002). aAI3061704
Murray-Coleman, J., Smith, A.: The automated measurement of BRDFS and their application to luminaire modeling. J. Illum. Eng. Soc. 19(1), 87–99 (1990). https://doi.org/10.1080/00994480.1990.10747944
Rump, M., Mueller, G., Sarlette, R., Koch, D., Klein, R.: Photo-realistic rendering of metallic car paint from image-based measurements. Comput. Graphics Forum 27(2), 527–536 (2008). https://doi.org/10.1111/j.1467-8659.2008.01150.x
Tunwattanapong, B., et al.: Acquiring reflectance and shape from continuous spherical harmonic illumination. ACM Trans. Graph. 32(4) (2013). https://doi.org/10.1145/2461912.2461944
Wang, J., Zhao, S., Tong, X., Snyder, J., Guo, B.: Modeling anisotropic surface reflectance with example-based microfacet synthesis. ACM Trans. Graph. 27(3), 1–9 (2008). https://doi.org/10.1145/1360612.1360640
Ward, G.J.: Measuring and modeling anisotropic reflection. SIGGRAPH Comput. Graph. 26(2), 265–272 (1992). https://doi.org/10.1145/142920.134078
Yu, J., Xu, Z., Mannino, M., Jensen, H.W., Ramamoorthi, R.: Sparse sampling for image-based SVBRDF acquisition. In: Klein, R., Rushmeier, H. (eds.) Workshop on Material Appearance Modeling. The Eurographics Association (2016). https://doi.org/10.2312/mam.20161251
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Tun, Z.Z., Tsunezaki, S., Komuro, T., Yamamoto, S., Tsumura, N. (2020). A Portable Measurement System for Spatially-Varying Reflectance Using Two Handheld Cameras. In: Stephanidis, C., Chen, J.Y.C., Fragomeni, G. (eds) HCI International 2020 – Late Breaking Papers: Virtual and Augmented Reality. HCII 2020. Lecture Notes in Computer Science(), vol 12428. Springer, Cham. https://doi.org/10.1007/978-3-030-59990-4_20
Download citation
DOI: https://doi.org/10.1007/978-3-030-59990-4_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-59989-8
Online ISBN: 978-3-030-59990-4
eBook Packages: Computer ScienceComputer Science (R0)