Paper Info
Title
A Statistical Method for SVBRDF Approximation from Video Sequences in General Lighting Conditions
Abstract
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. © 2012 Wiley Periodicals, Inc.
Year
DOI
Venue
2012
10.1111/j.1467-8659.2012.03145.x
Comput. Graph. Forum
Keywords
Field
DocType
general lighting conditions,video sequences,statistical method,approximated svbrdf,diffuse color,statistical analysis,acquisition phase,acquisition scene,phong model,svbrdf approximation,object surface appearance,color sample,video sequence,bidirectional reflectance distribution function,shading
Bidirectional reflectance distribution function,Computer vision,Computer graphics (images),Computer science,Specular reflection,Complex geometry,Artificial intelligence,Rendering (computer graphics),Reflectivity,Computer graphics,Reflection mapping,Statistical analysis
Journal
Volume
Issue
ISSN
31
4
0167-7055
Citations 
PageRank 
References 
14
0.59
29
Authors
4
Name
Order
Citations
PageRank
Gianpaolo Palma1364.58
Marco Callieri227722.75
Matteo Dellepiane337930.85
Roberto Scopigno43056236.09