  The standard photometric stereo model makes several assumptions that are
rarely verified in experimental datasets. In particular, the observed object
should behave as a Lambertian reflector and the light sources should be
positioned at an infinite distance from it, along a known direction. Even when
Lambert's law is approximately fulfilled, an accurate assessment of the
relative position between the light source and the target is often unavailable
in real situations. The Hayakawa procedure is a computational method for
estimating such information directly from the data images. It occasionally
breaks down when some of the available images excessively deviate from
ideality. This is generally due to observing a non Lambertian surface, or
illuminating it from a close distance, or both. Indeed, in narrow shooting
scenarios, typical, e.g., of archaeological excavation sites, it is impossible
to position a flashlight at a sufficient distance from the observed surface. It
is then necessary to understand if a given dataset is reliable and which images
should be selected to better reconstruct the target. In this paper, we propose
some algorithms to perform this task and explore their effectiveness.
