3-D Reconstruction of Shaded Objects from Multiple Images Under Unknown Illumination |
| |
Authors: | Hailin Jin Daniel Cremers Dejun Wang Emmanuel Prados Anthony Yezzi Stefano Soatto |
| |
Affiliation: | 1.Office of Technology,Adobe Systems Incorporated,San Jose,USA;2.Dept. of Computer Science,Bonn,Germany;3.INRIA Rh?ne-Alpes,Montbonnot,France;4.School of Electrical and Computer Engineering,Georgia Institute of Technology,Atlanta,USA;5.Computer Science Department,University of California,Los Angeles,USA |
| |
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. We develop a
new model that explicitly enforces positivity in the light sources with the assumption that the object is Lambertian and its
albedo is piecewise constant and show that the new model significantly improves the accuracy and robustness relative to existing
approaches. |
| |
Keywords: | Stereoscopic segmentation Shape from shading Multi-view stereo Variational 3D reconstruction Level set methods Lighting and appearance reconstruction |
本文献已被 SpringerLink 等数据库收录! |
|