Abstract
This paper describes an algorithm to obtain local surface orientation from the apparent surface-pattern distortion in an image. We propose a spherical projection to model perspective imaging. A mapping is defined based on the measurement of the local distortions of a repeated known texture pattern due to the image projection. This mapping maps an apparent shape on the image sphere to a locus of possible surface orientations on the Gaussian sphere. An iterative constraint propagation algorithm with the orientations at occluding boundaries reduces possible surface orientations to a unique orientation. This algorithm can recover local surface orientation as well as interpolate surface orientations where no information is available. This algorithm is applied to a real image to demonstrate its performance.
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