Cloud Motion as a Calibration Cue

We propose cloud motion as a natural scene cue that enables geometric calibration of static outdoor cameras. This work introduces several new methods that use observations of an outdoor scene over days and weeks to estimate radial distortion, focal length and geo-orientation. Cloud-based cues provide strong constraints and are an important alternative to methods that require specific forms of static scene geometry or clear sky conditions. Our method makes simple assumptions about cloud motion and builds upon previous work on motion-based and line-based calibration. We show results on real scenes that highlight the effectiveness of our proposed methods.