  Shape from texture refers to the extraction of 3D information from 2D images
with irregular texture. This paper introduces a statistical framework to learn
shape from texture where convex texture elements in a 2D image are represented
through a point process. In a first step, the 2D image is preprocessed to
generate a probability map corresponding to an estimate of the unnormalized
intensity of the latent point process underlying the texture elements. The
latent point process is subsequently inferred from the probability map in a
non-parametric, model free manner. Finally, the 3D information is extracted
from the point pattern by applying a locally scaled point process model where
the local scaling function represents the deformation caused by the projection
of a 3D surface onto a 2D image.
