Abstract
Several techniques have been developed for recovering reflectance
properties of real surfaces under unknown illumination. However,
in most cases, those techniques assume that the light sources are
located at inifinity, which cannot be applied safely to, for example,
reflectance modeling of indoor environments. In this paper, we propose
two types of methods to estimate the surface reflectance property
of an object, as well as the position of a light source from a single
view without the distant illumination assumption, thus relaxing the
conditions in the previous methods. Given a real image and a 3D geometric
model of an object with specular reflection as inputs, the first
method estimates the light source position by fitting to the Lambertian
diffuse component, while separating the specular and diffuse components
by using an iterative relaxation scheme. Our second method extends
that first method by using as input a specular component image, which
is acquired by analyzing multiple polarization images taken from
a single view, thus removing its constraints on the diffuse reflectance
property. This method simultaneously recovers the reflectance properties
and the light source positions by optimizing the linearity of a log-transformed
Torrance-Sparrow model. By estimating the object's reflectance property
and the light source position, we can freely generate synthetic images
of the target object under arbitrary lighting conditions with not
only source direction modification but also source-surface distance
modification. Experimental results show the accuracy of our estimation
framework.
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