Skip to main content
SpringerLink
Log in

Appearance Sampling of Real Objects for Variable Illumination

  • Published:
International Journal of Computer Vision Aims and scope Submit manuscript

Abstract

The appearance of an object greatly changes under different lighting conditions. Even so, previous studies have demonstrated that the appearance of an object under varying illumination conditions can be represented by a linear subspace. A set of basis images spanning such a linear subspace can be obtained by applying the principal component analysis (PCA) for a large number of images taken under different lighting conditions. Since little is known about how to sample the appearance of an object in order to correctly obtain its basis images, it was a common practice to use as many input images as possible. In this study, we present a novel method for analytically obtaining a set of basis images of an object for varying illumination from input images of the object taken properly under a set of light sources, such as point light sources or extended light sources. Our proposed method incorporates the sampling theorem of spherical harmonics for determining a set of lighting directions to efficiently sample the appearance of an object. We further consider the issue of aliasing caused by insufficient sampling of the object's appearance. In particular, we investigate the effectiveness of using extended light sources for modeling the appearance of an object under varying illumination without suffering the aliasing caused by insufficient sampling of its appearance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Basri, R. and Jacobs, D. 2001. Lambertian reflectance and linear subspaces. In Proc. IEEE Int. Conf. Computer Vision 01, pp. 383–389.

  • Debevec, P. 1998. Rendering synthetic objects into real scenes: Bridging traditional and image-based graphics with global illumination with high dynamic range photography. In Proc. SIGGRAPH 98, pp. 189–198.

  • Driscoll, J. and Healy Jr., D. 1994. Computing Fourier transforms and convolutions on the 2-sphere. J. Advanced in Applied Mathematics, 15:202–250.

  • Epstein, R., Hallinan, P., and Yuille, A. 1995. 5+/−2 eigenimages suffice: An empirical investigation of low-dimensional lighting models. In Proc. IEEE Workshop on Physics-Based Modeling in Computer Vision, pp. 108–116.

  • Georghiades, A., Kriegman, D., and Belhumeur, P. 1998. Illumination cones for recognition under variable lighting: Faces. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 52–59.

  • Georghiades, A., Kriegman, D., and Belhumeur, P. 2001. From few to many: Generative models for recognition under variable pose and illumination. IEEE Trans. Pattern Analysis and Machine Intelligence, 23(6):643–660.

    Article  Google Scholar 

  • Hallinan, P. 1994. A low-dimensional representation of human faces for arbitrary lighting conditions. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 995–999.

  • http://healpix.jpl.nasa.gov/

  • Lee, K.C., Ho, J., and Kriegman, D. 2001. Nine points of light: Acquiring subspaces for face recognition under variable lighting. In Proc. IEEE Conf. Computer Vision and Pattern Recognition 01, pp. 519–526.

  • Malzbender, T., Gelb, D., and Wolters, H. 2001. Polynomial texture maps. In Proc. SIGGRAPH 01, pp. 519–528.

  • Mohlenkamp, M.J. 1999. A fast transform for spherical harmonics. J. Fourier Analysis and Applications, 5(2/3):159–184.

    Article  MATH  Google Scholar 

  • Murase, H. and Nayar, S. 1995. Visual learning and recognition of 3-D objects from appearance. Int. J. Computer Vision, 14(1):5–24.

    Article  Google Scholar 

  • Nayar, S.K., Ikeuchi, K., and Kanade, T. 1991. Surface reflection: Physical and geometrical perspectives. IEEE Trans. Pattern Analysis and Machine Intelligence, 13(7):611–634.

    Article  Google Scholar 

  • Nayar, S.K., Ikeuchi, K., and Kanade, T. 1990. Determining shape and reflectance of hybrid surfaces by photometric sampling. IEEE Trans. Robotics and Automation, 6(4):418–443.

    Article  Google Scholar 

  • Nishino, K., Zhang, Z., and Ikeuchi, K. 2001. Determining reflectance parameters and illumination distribution from sparse set of images for view-dependent image synthesis. In Proc. IEEE Int. Conf. Computer Vision 01.

  • Ngan, A., Durand, F., and Matusik, W. 2005. Experimental analysis of BRDF models. In Proc. the Eurographics Symposium on Rendering, pp. 117–226.

  • Okabe, T., Sato, I., and Sato, Y. 2004. Spherical harmonics vs. haar wavelets: Basis for recovering illumination from cast shadows. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. I-50–57.

  • Press, W.H., Flannery, B.P., Teukolsky, S.A., and Vetterling, W.T. 1988. Numerical Recipes in C: The Art of Scientific Computing. Cambridge University Press: Cambridge.

    MATH  Google Scholar 

  • Ramamoorthi, R. and Hanrahan, P. 2001a. A signal-procession framework for inverse rendering. In Proc. SIGGRAPH 01, pp. 117–128.

  • Ramamoorthi, R. and Hanrahan, P. 2001b. On the relationship between radiance and irradiance: Determining the illumination from images of a convex lambertian object. J. Optical Society of America A, 18(10):2448–2459.

    Google Scholar 

  • Ramamoorthi, R. and Hanrahan, P. 2001c. An efficient representation for irradiance environment maps. In Proc. SIGGRAPH 01, pp. 497–500.

  • Ramamoorthi, R. and Hanrahan, P. 2002. Frequency space environment map rendering. In Proc. SIGGRAPH 02, pp. 517–526.

  • Ramamoorthi, R., Koudelka, M., and Belhumeur, P. 2005. Fourier theory for cast shadows. IEEE Trans. PAMI, 27(2):288–295.

    Google Scholar 

  • Sato, I., Okabe, T., Sato, Y., and Ikeuchi, K. 2003. Appearance sampling for obtaining a set of basis images for variable illumination. In Proc. IEEE Int. Conf. Computer Vision, pp. 800–807.

  • Sato, I., Okabe, T., Sato, Y., and Ikeuchi, K. 2005. Using extended light sources for modeling object appearance under varying illumination. In Proc. IEEE Int. Conf. Computer Vision, pp. 325–332.

  • Schechner, Y., Nayar, S., and Belhumeur, P. 2003. A theory of multiplexed illumination. In Proc. IEEE Int. Conf. Computer Vision, pp. 808–815.

  • Schroder, P. and Sweldens, W. 1995. Spherical Wavelets: efficiently representing functions on the sphere. In Proc. SIGGRAPH 95, pp. 161–172.

  • Shim, K. and Chen, T. 2004. Efficient representation of lighting patterns for image-based relighting. In Proc. Picture Coding Symposium.

  • Shashua, A. 1997. On photometric issues in 3D visual recognition from a single image. Int. J. Computer Vision, 21:99–122.

    Google Scholar 

  • Sloan, P., Kautz, J., and Snyder, J. 2002. Precomputed radiance transfer for real-time rendering in dynamic, low-frequency lighting environments. In Proc. SIGGRAPH 02, pp. 527–536.

  • Ward, G.J. 1992. Measuring and modeling anisotropic reflection. In Proc. SIGGRAPH 92, pp. 265–272.

  • Westin, S., Arvo, J., and Torrance, K. 1992. Predicting reflectance functions from complex surfaces. In Proc. SIGGRAPH 92, pp. 255–264.

  • Yuille, A., Snow, D., Epstein, R., and Belhumeur, P. 1999. Determining generative models of objects under varying illumination: Shape and albedo from multiple images using SVD and integrability. Int. J. Computer Vision, 35(3):203–222.

    Article  Google Scholar 

  • Zhang, L. and Samaras, D. 2003. Face recognition under variable lighting using harmonic image exemplars. IEEE Conf. Computer Vision and Pattern Recognition, I:19–25.

  • Zhao, L. and Yang, Y. 1999. Theoretical analysis of illumination in PCA-based vision systems. Pattern Recognition, 32:547–564.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National Institute of Informatics, Tokyo, Japan

    Imari Sato

  2. The University of Tokyo, Tokyo, Japan

    Takahiro Okabe & Yoichi Sato

Authors
  1. Imari Sato
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Takahiro Okabe
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yoichi Sato
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Imari Sato.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sato, I., Okabe, T. & Sato, Y. Appearance Sampling of Real Objects for Variable Illumination. Int J Comput Vis 75, 29–48 (2007). https://doi.org/10.1007/s11263-007-0036-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11263-007-0036-1

Keywords

Search

Navigation