2017 CVPR CVPR 2017

Computational Imaging on the Electric Grid

Abstract

Night beats with alternating current (AC) illumination. By passively sensing this beat, we reveal new scene information which includes: the type of bulbs in the scene, the phases of the electric grid up to city scale, and the light transport matrix. This information yields unmixing of reflections and semi-reflections, nocturnal high dynamic range, and scene rendering with bulbs not observed during acquisition. The latter is facilitated by a database of bulb response functions for a range of sources, which we collected and provide. To do all this, we built a novel coded-exposure high-dynamic-range imaging technique, specifically designed to operate on the grid's AC lighting.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Computer Vision
🧭 Keyword Pioneer — image unmixing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization