When a scene is lit by a source of light, the radiance of each point in the
scene can be viewed as having two components, namely, direct and global. The
direct component is due to the direct illumination of the point by the source.
The global component is due to the illumination of the point by other points in
the scene. It is desirable to have a method for measuring the direct and global
components of a scene, as each component conveys important information about
the scene that cannot be inferred from their sum.& For instance, the direct
component gives us the purest measurement of how the material properties of a
scene point interact with the source and camera. Therefore, a method that can
measure just the direct component can be immediately used to enhance a wide
range of scene capture techniques that are used in computer vision and computer
graphics.& The global component conveys the complex optical interactions
between different objects and media in the scene.& It is the global component
that makes photorealistic rendering a hard and computationally intensive
problem. A measurement of this component could provide new insights into these
interactions that in turn could aid the development of more efficient rendering
The goal of this project is to develop efficient methods for separating the
direct and global components of a scene lit by a single light source and viewed
by a camera.& We show that the direct and global components at all scene points
can be efficiently measured by using high frequency illumination patterns.&
This approach does not require the scattering properties of the scene points to
be known. We only assume that the global contribution received by each scene
point is a smooth function with respect to the frequency of the lighting. This
assumption makes it possible, in theory, to do the separation by capturing just
two images taken with a dense binary illumination pattern and its complement.
In practice, due to the resolution limits imposed by the source and the camera,
a larger set of images (25 in our setting) is used. We show separation results
for several scenes that include diffuse and specular interreflections,
subsurface scattering due to translucent surfaces and volumetric scattering due
to dense media. We also show how the direct and global components can be used
to generate new images that represent changes in the optical properties of the
objects and the media in the scene.
We have developed several variants of our method that seek to minimize the
number of images needed for separation.& By using a sinusoid-based illumination
pattern, the separation can be done using just three images taken by changing
the phase of the pattern. When the resolution of the camera and the source are
greater than the desired resolution of the direct and global images, the
separation can be done with a single image by assuming neighboring scene points
to have similar direct and global components. In the case of just a simple
point light source, such as the sun, the source cannot be controlled to
generate the required high frequency illumination patterns.& In such cases, the
shadow of a line or mesh occluder can be swept over the scene while it is
captured by a video camera. The captured video can then be used to compute the
direct and global components. This project was done in collaboration with Michael
Grossberg at City
College of New York and Ramesh Raskar at MERL.
"Fast Separation of Direct and Global Components of a Scene using High Frequency Illumination,"
S.K. Nayar, G. Krishnan, M. D. Grossberg, R. Raskar,
ACM Trans. on Graphics (also Proc. of ACM SIGGRAPH),
[PDF] [bib] [©] [Project Page]
"Visual Chatter in the Real World,"
S. K. Nayar and G. Krishnan ,
Proceedings of Eurographics Symposium on Rendering,
[PDF] [bib] [©] [Project Page]
Gallery of Results:
We present a gallery of results obtained by applying our separation methods
to a wide variety of real scenes. The methods use shifted checkerboards, line
occluders, mesh occluders and separation from a single image. The scenes
include objects that produce strong interreflections, subsurface scattering,
volumetric scattering and light diffusion. For some of the scenes, we
show novel images computed using the separation results.
Examples of Video-Rate Separation:
We have extended our separation method to video. For this we have used a high
speed projector (MULE2A from Fakespace Labs) and a high speed camera. Here we
show the separation for two scenes - one which involves strong diffuse
interreflections and another which exhibits strong volumetric scattering.