Estimating Natural Illumination
from a Single Outdoor Image


From a single image (left), we estimate the most likely sky appearance (middle) and insert a 3-D object (right). Illumination estimation was done entirely automatically.

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Abstract

Virtual sun dial

Sun position probability

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.

Citation

Jean-François Lalonde, Alexei A. Efros, and Srinivasa G. Narasimhan. Estimating Natural Illumination from a Single Outdoor Image, International Conference on Computer Vision, 2009. [PDF] [BibTeX]

Talk

Download the slides from the talk given at ICCV 2009 in the following formats:

[MS Powerpoint, 27.3MB], export from Apple Keynote
[PDF, 37.6MB]
[Apple Keynote, 36.4MB], original version used at ICCV 2009.

Additional results

Please download supplementary results [PDF, 5.8MB].

Code

Here are some software packages relevant to that project:

Sky model

Funding

This research is supported by:

NSF CCF-0541230
NSF IIS-0546547
ONR N00014-08-1-0330
NSF IIS-0643628

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