A data-mining approach to 3D realistic render setup assistance

Autoren C. Gonzalez-Mocillo
L.M. Lopez
J.J. Castro-Schez
Bernhard Moser
Editoren K. Haigh
N. Rychtyckjy
Titel A data-mining approach to 3D realistic render setup assistance
Buchtitel Proceedings of the 21st Innovative Applications of Artificial Intelligence Conference IAAI 2009
Typ in Konferenzband
Verlag AAAI Press
Abteilung KVS
ISBN 978-1-57735-423-9
Monat July
Jahr 2009
Seiten 93-98
SCCH ID# 910
Abstract

Realistic rendering is the process of generating a 2D image from an abstract description of a 3D scene aiming to achieve a quality of a photo. The accuracy in the simulation of the interaction of light particles through the scene requires different rendering methods. According to the current practice it is up to the user to choose optimal settings of input parameters for these algorithms in terms of time-efficiency as well as image quality. This is an iterative trial and error process, even for expert users. In contrast, this paper describes a novel approach based on techniques from the field of data-mining and genetic computing to assist the user in the selection of render parameters. Experimental results are presented which show the benefits of this approach.