CMU VASC Seminar: What does the sky tell us about the camera?

What does the sky tell us about the camera?
Jean-Francois Lalonde
Robotics Institute, Carnegie Mellon

VASC Seminar
Monday, November 10


Abstract: As the main observed illuminant outdoors, the sky is a rich source of information about the scene. However, it is yet to be fully explored in computer vision because its appearance in an image depends on the sun position, weather conditions, photometric and geometric parameters of the camera, and the location of capture. In this talk, I will present an analysis of two sources of information available within the visible portion of the sky region: the sun position, and the sky appearance. By fitting a model of the predicted sun position to an image sequence, we show how to extract camera parameters such as the focal length, and the zenith and azimuth angles. Similarly, we show how we can extract the same parameters by fitting a physically-based sky model to the sky appearance. In short, the sun and the sky serve as geometric calibration targets, which can be used to annotate a large database of image sequences. We use our methods to calibrate 22 real, low-quality webcam sequences scattered throughout the continental US, and show deviations below 4% for focal length, and 3 degrees for the zenith and azimuth angles. Once the camera parameters are recovered, we use them to define a camera-invariant sky appearance model, which we exploit in two applications: 1) segmentation of the sky and cloud layers, and 2) data-driven sky matching across different image sequences based on a novel similarity measure defined on sky parameters. This measure, combined with a rich appearance database, allows us to model a wide range of sky conditions.

Bio: Jean-Francois Lalonde received his B.E. in Computer Engineering from Laval University, Canada in 2004. He received his M.S. in Robotics from Carnegie Mellon University in 2006 under Martial Hebert, and he has been a Robotics Ph.D. student advised by Alexei A. Efros in that institution since. His research interests are in computer vision and computer graphics, focusing on image understanding and synthesis
leveraging large amounts of data.