Local Shading Analysis

Local analysis of image shading, in the absence of prior knowledge about the viewed scene, may be used to provide information about the scene. The following has been proved. Every image point has the same image intensity and first and second derivatives as the image of some point on a Lambertian surface with principal curvatures of equal magnitude. Further, if the principal curvatures are assumed to be equal there is a unique combination of image formation parameters (up to a mirror reversal) that will produce a particular set of image intensity and first and second derivatives. A solution for the unique combination of surface orientation, etc., is presented. This solution has been extended to natural imagery by using general position and regional constraints to obtain estimates of the following: ¿ surface orientation at each image point; ¿ the qualitative type of the surface, i.e., whether the surface is planar, cylindrical, convex, concave, or saddle; ¿ the illuminant direction within a region. Algorithms to recover illuminant direction and estimate surface orientation have been evaluated on both natural and synthesized images, and have been found to produce useful information about the scene.

[1]  S. W. Kuffler.  Discharge patterns and functional organization of mammalian retina. , 1953, Journal of neurophysiology.

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

[3]  D. H. Kelly.  Spatial frequency selectivity in the retina , 1975, Vision Research.

[4]  P. Schiller,et al.  Quantitative studies of single-cell properties in monkey striate cortex. I. Spatiotemporal organization of receptive fields. , 1976, Journal of neurophysiology.

[5]  D. Hubel,et al.  Ferrier lecture - Functional architecture of macaque monkey visual cortex , 1977, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[6]  Gwyneth Thurgood,et al.  Magnifications: Photography With the Scanning Electron Microscope , 1977 .

[7]  D. Rose.  Mechanisms underlying the receptive field properties of neurons in cat visual cortex , 1979, Vision Research.

[8]  John R. Kender,et al.  Shape from Texture: An Aggregation Transform that Maps a Class of Textures into Surface Orientation , 1979, IJCAI.

[9]  E. Yund,et al.  Responses of striate cortex cells to grating and checkerboard patterns. , 1979, The Journal of physiology.

[10]  D. H. Kelly.  Motion and vision. II. Stabilized spatio-temporal threshold surface. , 1979, Journal of the Optical Society of America.

[11]  J. Daugman.  Two-dimensional spectral analysis of cortical receptive field profiles , 1980, Vision Research.

[12]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[13]  Katsushi Ikeuchi,et al.  Numerical Shape from Shading and Occluding Boundaries , 1981, Artif. Intell..

[14]  A. Pentland.  Finding the illuminant direction , 1982 .

[15]  A. Pentland.  The visual inference of shape : computation from local features , 1982 .

[16]  Grahame B. Smith.  Shape from Shading: An Assessment , 1983 .