Authors:
Toshiki Hirao
;
Ryo Kawahara
and
Takahiro Okabe
Affiliation:
Department of Artificial Intelligence, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan
Keyword(s):
Relighting, Display-Camera System, Specular Reflection, Extended Light Sources, End-fo-End Optimization.
Abstract:
Relighting real scenes/objects is useful for applications such as augmented reality and mixed reality. In general, relighting of glossy objects requires a large number of images, because specular reflection components are sensitive to light source positions/directions, and then the linear interpolation with sparse light sources does not work well. In this paper, we make use of not only point light sources but also extended light sources for efficiently capturing specular reflection components and achieve relighting from a small number of images. Specifically, we propose a CNN-based method that simultaneously learns the illumination module (illumination condition), i.e. the linear combinations of the point light sources and the extended light sources under which a small number of input images are taken and the reconstruction module which recovers the images under arbitrary point light sources from the captured images in an end-to-end manner. We conduct a number of experiments using re
al images captured with a display-camera system, and confirm the effectiveness of our proposed method.
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