Estimating Natural Illumination from a Single Outdoor Image

Jean-Francois Lalonde, Alexei A. Efros, and Srinivasa G. Narasimhan
IEEE International Conference on Computer Vision, October, 2009.


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Abstract
Given a single outdoor image, we present a method for estimating the likely illumination conditions of the scene. In particular, we compute the probability distribution over the sun position and visibility. The method relies on a combination of weak cues that can be extracted from different portions of the image: the sky, the vertical surfaces, and the ground. While no single cue can reliably estimate illumination by itself, each one can reinforce the others to yield a more robust estimate. This is combined with a data-driven prior computed over a dataset of 6 million Internet photos. We present quantitative results on a webcam dataset with annotated sun positions, as well as qualitative results on consumer- grade photographs downloaded from Internet. Based on the estimated illumination, we show how to realistically insert synthetic 3-D objects into the scene.

Notes
Associated Center(s) / Consortia: Vision and Autonomous Systems Center
Associated Lab(s) / Group(s): Illumination and Imaging Lab and Computer Graphics Lab

Text Reference
Jean-Francois Lalonde, Alexei A. Efros, and Srinivasa G. Narasimhan, "Estimating Natural Illumination from a Single Outdoor Image," IEEE International Conference on Computer Vision, October, 2009.

BibTeX Reference
@inproceedings{Lalonde_2009_6483,
   author = "Jean-Francois Lalonde and Alexei A. Efros and Srinivasa G Narasimhan",
   title = "Estimating Natural Illumination from a Single Outdoor Image",
   booktitle = "IEEE International Conference on Computer Vision",
   month = "October",
   year = "2009",
}