Accession Number : ADA327858
Title : Local Shape from Specularity,
Corporate Author : STANFORD UNIV CA DEPT OF COMPUTER SCIENCE
Personal Author(s) : Healey, Glenn ; Binford, Thomas O.
PDF Url : ADA327858
Report Date : JUN 1986
Pagination or Media Count : 30
Abstract : 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 specular reflectance models which have been used in computer vision and graphics. For our work, we adopt the Torrance-Sparrow specular model which, unlike most previous models, considers the underlying physics of specular reflection from rough surfaces. From this model we derive powerful relationships between the properties of a specular feature in an image and local properties of the corresponding surface. We show how this analysis can be used for both prediction and interpretation in a vision system. A shape from specularity system has been implemented to test our approach. The performance of the system is demonstrated by careful experiments with specularly reflecting objects.
Descriptors : *MODELS, *SURFACE ROUGHNESS, *SPECULAR REFLECTION, SHAPE, SURFACES, PHYSICS, IMAGES, COMPUTER VISION, REFLECTANCE.
Subject Categories : Optics
Distribution Statement : APPROVED FOR PUBLIC RELEASE