Shape from texture from a multi-scale perspective

Abstract

The problem of scale in shape from texture is addressed. The need for two scale parameters is emphasized: a local scale, for describing the amount of smoothing used for suppressing noise and irrelevant details when computing primitive texture descriptors from image data; and an integration scale, for describing the size of the region in space over which the statistics of the local descriptors is accummulated. The proposed computational model is expressed completely in terms of different invariants defined from Gaussian derivatives at multiple scales in scale-space. The resulting texture description can be combined with various assumptions about surface texture to estimate local surface orientation. Two specific assumptions, weak isotropy and constant area, are explored in more detail. Results from experiments on real and synthetic reference data with known geometry that demonstrate the viability of the approach are presented.