Shape Representations from Shading Primitives

Diffuse interreflections mean that surface shading and shape are related in ways that are difficult to untangle; in particular, distant and invisible surfaces may affect the shading field that one sees. The effects of distant surfaces are confined to relatively low spatial frequencies in the shading field, meaning that we can expect signatures, called shading primitives, corresponding to shape properties. We demonstrate how these primitives can be used to support the construction of useful shape representations. Approaches to this include testing hypotheses of geometric primitives for consistency with the shading field, and looking for shading events that are distinctive of some shape event. We show that these approaches can be composed, leading to an attractive process of representation that is intrinsically bottom up. This representation can be extracted from images of real scenes, and that the representation is diagnostic.

[1]  S. M. Shape-from-shading on a cloudy day , 1992 .

[2]  Terrance E. Boult,et al.  Recovery of SHGCs From a Single Intensity View , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[4]  M. Brady,et al.  Smoothed Local Symmetries and Their Implementation , 1984 .

[5]  D. Marr,et al.  Representation and recognition of the spatial organization of three-dimensional shapes , 1978, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[6]  David A. Forsyth,et al.  Reflections on Shading , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Steven W. Zucker,et al.  Diffuse shading, visibility fields, and the geometry of ambient light , 1993, 1993 (4th) International Conference on Computer Vision.

[8]  Federico Girosi,et al.  Training support vector machines: an application to face detection , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  Jun Yang,et al.  Determining a polyhedral shape using interreflections , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[10]  Berthold K. P. Horn SHAPE FROM SHADING: A METHOD FOR OBTAINING THE SHAPE OF A SMOOTH OPAQUE OBJECT FROM ONE VIEW , 1970 .

[11]  David A. Forsyth,et al.  Shading primitives: finding folds and shallow grooves , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[12]  J. Koenderink,et al.  Geometrical modes as a general method to treat diffuse interreflections in radiometry , 1983 .

[13]  Tomaso A. Poggio,et al.  Pedestrian detection using wavelet templates , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[14]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[15]  Robert J. Woodham,et al.  Photometric method for determining surface orientation from multiple images , 1980 .

[16]  Takashi Matsuyama,et al.  Shape from shading with interreflections under proximal light source-3D shape reconstruction of unfolded book surface from a scanner image , 1995, Proceedings of IEEE International Conference on Computer Vision.

[17]  E. Land,et al.  Lightness and retinex theory. , 1971, Journal of the Optical Society of America.

[18]  David A. Forsyth,et al.  Body plans , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[19]  I. Biederman Recognition-by-components: a theory of human image understanding. , 1987, Psychological review.

[20]  Andrew Blake,et al.  Boundary conditions for lightness computation in Mondrian World , 1985, Comput. Vis. Graph. Image Process..

[21]  Ramakant Nevatia,et al.  Description and Recognition of Curved Objects , 1977, Artif. Intell..