A growing trend in computer vision has been the use of physical reflectance models,
predicting reflected radiant intensity and color, to obtain constraints on object features. Until …

A computationally simple yet powerful method for distinguishing metal and dielectric
material surfaces from the polarization characteristics of specularly reflected light is …

Abstract Machine vision can greatly benefit from the development of accurate reflectance
models. There are two approaches to the study of reflection: physical and geometrical optics …

We propose a method for measuring surface shapes of transparent objects by using a
polarizing filter. Generally, the light reflected from an object is partially polarized. The degree …

In this paper, we present an approach to color image understanding that can be used to
segment and analyze surfaces with color variations due to highlights and shading. The work …

Techniques for modeling an object through observation are very important in object
recognition and virtual reality. A wide variety of techniques have been developed for …

A simple and stable method is proposed for distinguishing dielectric and metal material
surfaces from the polarization images captured by a vision system consisting of a linear …

Human and machine visual sensing is enhanced when surface properties of objects in
scenes, including color, can be reliably estimated despite changes in the ambient lighting …

Many algorithms in computer vision assume diffuse only reflections and deem specular
reflections to be outliers. However, in the real world, the presence of specular reflections is …

We show that highlights in images of objects with specularly reflecting surfaces provide
significant information about the surfaces which generate them. A brief survey is given of …