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