| Author(s) |
C. Gonzalez-Mocillo
L.M. Lopez
J.J. Castro-Schez
Bernhard Moser
|
| Title |
A data-mining approach to 3D realistic render setup assistance |
| Booktitle |
Proceedings of the 21st Innovative Applications of Artificial Intelligence Conference IAAI 2009 |
| Typ |
Inproceedings |
| Month |
July |
| Year |
2009 |
| Pages |
93-98 |
| Editor(s) |
K. Haigh, N. Rychtyckjy |
| Publisher |
AAAI Press |
| ISBN |
978-1-57735-423-9 |
| SCCH # |
0910 |
| 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. |