Title:
Shedding Light on Stereoscopic Segmentation
Shedding Light on Stereoscopic Segmentation
Author(s)
Jin, Hailin
Cremers, Daniel
Yezzi, Anthony
Soatto, Stefano
Cremers, Daniel
Yezzi, Anthony
Soatto, Stefano
Advisor(s)
Editor(s)
Collections
Supplementary to
Permanent Link
Abstract
We propose a variational algorithm to jointly estimate the
shape, albedo, and light configuration of a Lambertian
scene from a collection of images taken from different vantage
points. Our work can be thought of as extending classical
multi-view stereo to cases where point correspondence
cannot be established, or extending classical shape from
shading to the case of multiple views with unknown light
sources. We show that a first naive formalization of this
problem yields algorithms that are numerically unstable, no
matter how close the initialization is to the true geometry.
We then propose a computational scheme to overcome this
problem, resulting in provably stable algorithms that converge
to (local) minima of the cost functional. Although we
restrict our attention to Lambertian objects with uniform
albedo, extensions of our framework are conceivable.
Sponsor
Date Issued
2004-06
Extent
Resource Type
Text
Resource Subtype
Proceedings