Title :
Shedding light on stereoscopic segmentation
Author :
Jin, Hailin ; Cremers, Daniel ; Yezzi, Anthony J. ; Soatto, Stefano
Author_Institution :
Dept. of Comput. Sci., California Univ., Los Angeles, CA, USA
fDate :
27 June-2 July 2004
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.
Keywords :
albedo; computational geometry; convergence; image reconstruction; image segmentation; light sources; minimisation; stereo image processing; variational techniques; Lambertian scene; albedo; convergence; cost function; geometry; light configuration; light sources; local minima; multiview stereo; shape estimation; stereoscopic segmentation; variational algorithm; variational formalization; Computer science; Computer vision; Detectors; Geometry; Layout; Lighting; Reflection; Reflectivity; Shape; Stereo vision;
Conference_Titel :
Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on
Print_ISBN :
0-7695-2158-4
DOI :
10.1109/CVPR.2004.1315011