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Surface Reflectance Model Estimation from Daylight Illuminated Image Sequences.
Author(s) -
R.P. Love,
ND Efford
Publication year - 1995
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5244/c.9.32
Subject(s) - daylight , gloss (optics) , computer vision , artificial intelligence , computer science , reflection (computer programming) , reflectivity , position (finance) , optics , bidirectional reflectance distribution function , light reflection , surface (topology) , standard illuminant , remote sensing , computer graphics (images) , mathematics , geology , physics , materials science , geometry , finance , economics , composite material , programming language , coating
Accurate surface reflection models derived from existing natural scenes can be used for a variety of tasks. This paper presents a machine vision approach for determining such models. We investigate the use of simplistic models of reflection and daylight illumination to determine surface reflection properties. We attempt to determine the gloss factor of both an individual surface and a multi-faceted object when illuminated by natural light with varying sun position. Experiments are performed using synthetic image sequences of surfaces illuminated by CIE standard clear and intermediate skies, viewed from a variety of camera positions. Results show that some success can be achieved using such simple illumination models. Enhancements to the proposed method are also discussed with a view to improving system performance.

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