Planar surface orientation from texture spatial frequencies

Abstract This paper presents a computational model and a practical algorithm for determining the three-dimensional orientation of a planar surface from visual texture information. The model consists of three parts: (1) a local spatial frequency based texture representation; (2) a model describing the projection of surface texture to image texture; and (3) a solution of the texture projection model for the surface orientation under an assumption of surface texture homogeneity. The algorithm first measures the dominant frequency at each image point using three wavelet-like transforms, and then finds the surface orientation that minimizes the variance of the image frequencies' backprojections. The algorithm is tested on photographs of real-world surfaces, exhibiting an average accuracy of better than 3° in slant and 4° in tilt. The current model and algorithm are more accurate, yet substantially simpler, than earlier versions of this approach.

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