Shape from Regular Patterns: An Example of Constraint Propagation in Vision

Abstract

An algorithm is proposed for obtaining local surface orientation from the apparent distortion of surface patterns in an image. A spherical projection is used for imaging. A mapping is defined from points on this image sphere to a locus of points on the Gaussian sphere which corresponds to possible surface orientations. This mapping is based on the measurement of the local distortions of a repeated known texture pattern due to the imaging projection. This locus of possible surface orientations can be reduced to a unique orientation at each point on the image sphere using 3 vantage points and taking the intersection of the loci of possible orientations derived from each vantage. It is also possible to derive a unique surface orientation at each image point through the use of an iterative constraint propagation technique along with the orientation information available at occluding boundaries. Both method are demonstrated for real images.