A Statistical Technique for Recovering Surface Orientation from Texture in Natural Imagery

A statistical method is reported for inferring the shape and orientation of irregularly marked surfaces using image geometry. The basis for solving this problem lies in an understanding of projective geometry, coupled with simple statistical models of the contour generating process. This approach is first applied to the special case of surfaces known to be planar. The distortion of contour shape imposed by projection is treated as a signal to be estimated, and variations of non-projective origin are treated as noise. The resulting method is next extended to the estimation of curved surfaces, and applied successfully to natural images. The statistical estimation strategy is then experimentally compared to human perception of orientation: human observers' judgements of tilt correspond closely to the estimates produced by the planar strategy.