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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Lighting Estimation in Indoor Environments from Low-Quality Images
verfasst von : Natalia Neverova, Damien Muselet, Alain Trémeau
Erschienen in: Computer Vision – ECCV 2012. Workshops and Demonstrations
Verlag: Springer Berlin Heidelberg
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Lighting conditions estimation is a crucial point in many applications. In this paper, we show that combining color images with corresponding depth maps (provided by modern depth sensors) allows to improve estimation of positions and colors of multiple lights in a scene. Since usually such devices provide low-quality images, for many steps of our framework we propose alternatives to classical algorithms that fail when the image quality is low. Our approach consists in decomposing an original image into specular shading, diffuse shading and albedo. The two shading images are used to render different versions of the original image by changing the light configuration. Then, using an optimization process, we find the lighting conditions allowing to minimize the difference between the original image and the rendered one.