Variable albedo surface reconstruction from stereo and shape from shading
Year: 2002
Type: conference-paper
Abstract: We present a multiview method for the computation of object shape and reflectance characteristics based on the integration of shape from shading (SFS) and stereo, for nonconstant albedo and non-uniformly Lambertian surfaces. First we perform stereo fitting on the input stereo pairs or image sequences. When the images are uncalibrated, we recover the camera parameters using bundle adjustment. Eased on the stereo result, we can automatically segment the albedo map (which is taken to be piece-wise constant) using a minimum description length (MDL) based metric, to identify areas suitable for SFS (typically smooth textureless areas) and to derive illumination information. The shape and the illumination parameter estimates are refined using a deformable model SFS algorithm, which iterates between computing shape and illumination parameters. Our method takes into account the viewing angle dependent for shortening and specularity effects, and compensates as much as possible by utilizing information from more than one images. We demonstrate that we can extend the applicability of SFS algorithms to real world situations when some of its traditional assumptions are violated. We demonstrate our method by applying it to face shape reconstruction. Experimental results indicate a significant improvement over SFS-only or stereo-only based reconstruction. Model accuracy and detail are improved, especially in areas of low texture detail. Albedo information is retrieved and can be used to accurately re-render the model under different illumination conditions.
Authors: D. Samaras, D. Metaxas, P. Fua, Y.G. Leclerc
Language: English
Topic: Advanced Vision and Imaging
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2110059470