|
Image based Relighting(IBRL) has attracted a lot of interest in
the computer graphics research, gaming, and virtual cinematography
communities for its ability to relight objects or scenes, from
novel illuminations captured in natural or synthetic
environments. However, the advantages of an image-based framework
conflicts with a drastic increase in the storage caused by the
huge number of reference images pre-captured under various
illumination conditions. To perform fast relighting, while
maintaining the visual fidelity, one needs to preprocess this huge
data into an appropriate model. |
|
In this paper, we propose a novel and efficient two-stage
relighting algorithm which creates a compact representation of the
huge IBRL dataset and facilitates fast relighting. In the first
stage, using Singular Value Decomposition, a set of eigen image
bases and relighting coefficients are computed. In the second
stage, and in contrast to prior methods, the correlation among the
relighting coefficients is harnessed using Spherical
Harmonics. The proposed method thus has lower memory and
computational requirements. We demonstrate our results
qualitatively and quantitatively with new generated image data.
|
