Visibility cameras
Nathan Graves, Shawn D. Newsam · 2012
This paper investigates image processing and pattern recognition techniques to estimate light extinction based on the visual content of images from static cameras. We propose two predictive models that incorporate multiple scene regions into the estimation: regression trees and multivariate linear regression. Incorporating multiple regions is important since regions at different distances are effective for estimating light extinction under different visibility regimes. We evaluate our models using a sizable dataset of images and ground truth light extinction values from a visibility camera system in Phoenix, Arizona.