HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Journal articles

3-D Reconstruction of Shaded Objects from Multiple Images Under Unknown Illumination

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.
Document type :
Journal articles
Complete list of metadata

Cited literature [40 references]  Display  Hide  Download

Contributor : Emmanuel Prados Connect in order to contact the contributor
Submitted on : Tuesday, March 4, 2008 - 11:08:32 AM
Last modification on : Thursday, February 3, 2022 - 3:09:45 AM
Long-term archiving on: : Friday, September 28, 2012 - 10:35:35 AM


Files produced by the author(s)



Hailin Jin, Daniel Cremers, Dejun Wang, Emmanuel Prados, Anthony Yezzi, et al.. 3-D Reconstruction of Shaded Objects from Multiple Images Under Unknown Illumination. International Journal of Computer Vision, Springer Verlag, 2008, 76 (3), pp.245-256. ⟨10.1007/s11263-007-0055-y⟩. ⟨inria-00260433⟩



Record views


Files downloads