Shape from shading
Integrability disambiguates surface recovery in two-image photometric stereo
International Journal of Computer Vision
Computer Vision and Image Understanding
Computer Vision and Image Understanding
Shape Reconstruction of 3D Bilaterally Symmetric Surfaces
International Journal of Computer Vision - Special issue on computer vision research at the Technion
Geotensity: Combining Motion and Lighting for 3D Surface Reconstruction
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A New Perspective [on] Shape-from-Shading
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
"Perspective Shape from Shading" and Viscosity Solutions
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Dense Shape Reconstruction of a Moving Object under Arbitrary, Unknown Lighting
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Photometric stereo for dynamic surface orientations
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
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We present a new method for recovering the 3D shape of a featureless smooth surface from three or more calibrated images. The main contribution of this paper is the ability to handle general images which are taken from unconstrained viewpoints and unconstrained illumination directions. To the best of our knowledge, no other method is currently capable of handling such images, since correspondence between such images is hard to compute. Our method combines geometric and photometric information in order to recover a dense correspondence between the images and successfully computes an accurate 3D shape of the surface. The method is based on a single pass and local computation and does not make use of global optimization over the whole surface. While we assume a Lambertian reflectance function, our method can be easily modified to handle more general reflectance models as long as it is possible to recover local normals from photometric information. Experimental results are presented for simulated and real images.