Passive Photometric Stereo from Motion

Jongwoo Lim, Jeffrey Ho, Ming-hsuan Yang, David Kriegman
ICCV 2005, to appear

Abstract
We introduce an iterative algorithm for shape reconstruction
from multiple images of a moving (Lambertian) object illuminated
by distant (and possibly time varying) lighting.  Starting with an
initial piecewise linear surface, the algorithm iteratively
estimates a new surface based on the previous surface estimate and
the photometric information available from the input image
sequence.  During each iteration, standard photometric stereo
techniques are applied to estimate the surface normals up to an
unknown generalized bas-relief transform, and a new surface is
computed by integrating the estimated normals. The algorithm
essentially consists of a sequence of matrix factorizations (of
intensity values) followed by minimization using gradient descent
(integration of the normals).  Conceptually, the algorithm admits
a clear geometric interpretation, which is used to provide a
qualitative analysis of the algorithm's convergence.
Implementation-wise, it is straightforward, being based on several
established photometric stereo and structure from motion
algorithms. We demonstrate experimentally the effectiveness of our
algorithm using several videos of hand-held objects moving in
front of a fixed light and camera.