Shape from Shading
Project Leader
Associate Professor
Mike Brooks.
Researchers
Rationale
Smooth variations in the brightness or shading of objects in an image
are often an important cue in human vision for estimating the shape of
depicted objects. This project is concerned with modelling this
process and setting up prototype systems for automatically recovering
surface shape from image shading: the results can potentially be
applied to the computer interpretation of satellite, medical and SAR
images, as well as automated visual inspection of industrial parts.
Description
Reconstructing shape from shading can be reduced to solving a
first-order, nonlinear partial differential equation. Challenges in
solving this problem are: to reduce the amount of prior information
required, such as knowledge of the light source direction; to develop
a robust, general-purpose solver; and to develop massively parallel
techniques. Our longer term aim is to fuse information from a
shape-from-shading solver with information from other "shape-from"
modules, in particular shape from stereo. We have selected this goal
as the capabilities of the differing modules are often complementary.
For example, shape from stereo works best on images exhibiting edges
and textures, whereas shape from shading performs optimally on images
exhibiting smooth brightness variation.
Status
CSSIP research into shape-from-shading concluded in 1996. This work
culminated in the development of a new direct method of computing shape
from shading based on merging multiple solutions derived from singular
points. The results of much of this work has now appeared in various
international journals (see publications information attached to main
page).
Back to VP home page
Last updated in May 1998 by Julian Magarey
(jfam@cssip.edu.au).
