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A Statistical Method for SVBRDF Approximation from Video Sequences in General Lighting Conditions
Author(s) -
Palma Gianpaolo,
Callieri Marco,
Dellepiane Matteo,
Scopigno Roberto
Publication year - 2012
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2012.03145.x
Subject(s) - computer science , computer vision , object (grammar) , artificial intelligence , specular reflection , function (biology) , computer graphics (images) , optics , physics , evolutionary biology , biology
We present a statistical method for the estimation of the Spatially Varying Bidirectional Reflectance Distribution Function (SVBRDF) of an object with complex geometry, starting from video sequences acquired with fixed but general lighting conditions. The aim of this work is to define a method that simplifies the acquisition phase of the object surface appearance and allows to reconstruct an approximated SVBRDF. The final output is suitable to be used with a 3D model of the object to obtain accurate and photo‐realistic renderings. The method is composed by three steps: the approximation of the environment map of the acquisition scene, using the same object as a probe; the estimation of the diffuse color of the object; the estimation of the specular components of the main materials of the object, by using a Phong model. All the steps are based on statistical analysis of the color samples projected by the video sequences on the surface of the object. Although the method presents some limitations, the trade‐off between the easiness of acquisition and the obtained results makes it useful for practical applications.