Shadows, Shading, and Projective Ambiguity

In a scene observed from a fixed viewpoint, the set of shadow curves in an image changes as a point light source (nearby or at infinity) assumes different locations. We show that for any finite set of point light sources illuminating an object viewed under either orthographic or perspective projection, there is an equivalence class of object shapes having the same set of shadows. Members of this equivalence class differ by a four parameter family of projective transformations, and the shadows of a transformed object are identical when the same transformation is applied to the light source locations. Under orthographic projection, this family is the generalized bas-relief (GBR) transformation, and we show that the GBR transformation is the only family of transformations of an object's shape for which the complete set of imaged shadows is identical. Furthermore, for objects with Lambertian surfaces illuminated by distant light sources, the equivalence class of object shapes which preserves shadows also preserves surface shading. Finally, we show that given multiple images under differing and unknown light source directions, it is possible to reconstruct an object's shape up to these transformations from the shadows alone.

[1]  M. Kemp The science of art : Optical themes in western art from Brunelleschi to Seurat , 1991 .

[2]  J J Koenderink,et al.  Affine structure from motion. , 1991, Journal of the Optical Society of America. A, Optics and image science.

[3]  Ramakant Nevatia,et al.  Detection of Buildings in Aerial Images Using Shape and Shadows , 1983, IJCAI.

[4]  David J. Kriegman,et al.  The Bas-Relief Ambiguity , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  R. Bruce Irvin,et al.  Methods for exploiting the relationship between buildings and their shadows in aerial imagery , 1989, IEEE Trans. Syst. Man Cybern..

[6]  Robert J. Woodham,et al.  Analysing Images of Curved Surfaces , 1981, Artif. Intell..

[7]  O. Faugeras Stratification of three-dimensional vision: projective, affine, and metric representations , 1995 .

[8]  A. Shashua Geometry and Photometry in 3D Visual Recognition , 1992 .

[9]  Andrew P. Within Intensity-based edge classification , 1982, AAAI 1982.

[10]  S. Ullman,et al.  Geometry and photometry in three-dimensional visual recognition , 1993 .

[11]  Dana H. Ballard,et al.  Computer Vision , 1982 .

[12]  Andrew Zisserman,et al.  Geometric invariance in computer vision , 1992 .

[13]  M. Baxandall Shadows and Enlightenment , 1995 .

[14]  David J. Kriegman,et al.  What is the set of images of an object under all possible lighting conditions? , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[15]  Ronen Basri,et al.  Recognition by Linear Combinations of Models , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  B. F. Cook The Elgin Marbles , 1984 .

[17]  Jan J. Koenderink,et al.  Affine structure and photometry , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[18]  R. Bruce Irvin,et al.  Methods For Exploiting The Relationship Between Buildings And Their Shadows In Aerial Imagery , 1989, Photonics West - Lasers and Applications in Science and Engineering.

[19]  Steven W. Zucker,et al.  What is a light source? , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[20]  Steven W. Zucker,et al.  Shadows and shading flow fields , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[21]  Berthold K. P. Horn,et al.  Determining Shape and Reflectance Using Multiple Images , 1978 .

[22]  E. Olszewski,et al.  Leonardo on Painting. , 1990 .

[23]  Michael Hatzitheodorou,et al.  The derivation of 3-D surface shape from shadows , 1989 .