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Conference Paper

Bayesian Relighting


Fuchs,  Martin
Computer Graphics, MPI for Informatics, Max Planck Society;
Computer Graphics, MPI for Informatics, Max Planck Society;


Blanz,  Volker
Computer Graphics, MPI for Informatics, Max Planck Society;


Seidel,  Hans-Peter       
Computer Graphics, MPI for Informatics, Max Planck Society;

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Fuchs, M., Blanz, V., & Seidel, H.-P. (2005). Bayesian Relighting. In O. Deussen, A. Keller, K. Bala, P. Dutré, D. W. Fellner, & S. N. Spencer (Eds.), Rendering Techniques 2005: Eurographics Symposium on Rendering Techniques (pp. 157-164). Aire-la-Ville, Switzerland: Eurographics Association.

Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-25ED-0
We present a simple method for relighting real objects viewed from a
fixed camera position. Instead of setting up a calibrated
measurement device, such as a light stage, we manually sweep a spotlight
over the walls of a white room, illuminating the object indirectly.
In contrast
to previous methods, we use arbitrary and unknown angular distributions of
incoming light. Neither the incident light nor the reflectance function
need to be represented explicitly in our approach.\\
The new method relies on images of a probe object, for instance a black
snooker ball, placed near the target object. Pictures of the probe in a novel
illumination are decomposed into a linear combination of measured images of
the probe. Then, a linear combination of images of the target object with the
same coefficients produces a synthetic image with the new illumination. We
use a simple Bayesian approach to find the most plausible output image, given
the picture of the probe and the statistics
observed in the dataset of samples.\\
Our results for a variety of novel illuminations, including synthetic lighting
by relatively narrow light sources as well as natural illuminations,
demonstrate that the new technique is a
useful, low cost alternative to existing techniques for a broad range of
objects and materials.