Variable albedo surface reconstruction from stereo and shape from shading

Dimitrios Samaras, Dimitris Metaxas, Pascal Fua, Yvan G. Leclerc

Research output: Contribution to journalConference articlepeer-review

66 Scopus citations


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 non-constant 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. Based 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 foreshortening 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.

Original languageEnglish (US)
Pages (from-to)480-487
Number of pages8
JournalProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
StatePublished - 2000
Externally publishedYes
EventIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2000 - Hilton Head Island, SC, USA
Duration: Jun 13 2000Jun 15 2000

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition


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