Abstract
Rainbows are a natural cue for calibrating outdoor imagery. While ephemeral, they provide unique calibration cues because they are centered exactly opposite the sun and have an outer radius of 42 degrees. In this work, we define the geometry of a rainbow and describe minimal sets of constraints that are sufficient for estimating camera calibration. We present both semi-automatic and fully automatic methods to calibrate a camera using an image of a rainbow. To demonstrate our methods, we have collected a large database of rainbow images and use these to evaluate calibration accuracy and to create an empirical model of rainbow appearance. We show how this model can be used to edit rainbow appearance in natural images and how rainbow geometry, in conjunction with a horizon line and capture time, provides an estimate of camera location. While we focus on rainbows, many of the geometric properties and algorithms we present also apply to other solar-refractive phenomena, such as parhelion, often called sun dogs, and the 22 degree solar halo.
Original language | English |
---|---|
Pages (from-to) | 820-835 |
Number of pages | 16 |
Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Volume | 8693 LNCS |
Issue number | PART 5 |
DOIs | |
State | Published - 2014 |
Event | 13th European Conference on Computer Vision, ECCV 2014 - Zurich, Switzerland Duration: Sep 6 2014 → Sep 12 2014 |
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science