Computational Imaging on the Electric Grid

Mark Sheinin, Yoav Y. Schechner and Kiriakos N. Kutulakos
Narrated overview video
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 (DELIGHT). To do all this, we introduce a novel coded-exposure high-dynamic-range imaging technique, specifically designed to operate on the grid’s AC lighting.

This camera system, which we built and demonstrate, is the ACam.

Publications
  1. Mark Sheinin, Yoav Y. Schechner and Kiriakos. N. Kutulakos, “Computational imaging on the electric grid,” To appear in Proc. IEEE CVPR (2017) Best Student Paper Award. (pdf)
     

  2. Mark Sheinin, Yoav Y. Schechner and Kiriakos. N. Kutulakos, “Computational imaging on the electric grid: Supplementary material,” Supplemental document in Proc. IEEE CVPR (2017), describing the DELIGHT database and some technical aspects. (pdf)

BibTex

@article{Sheinin:2017:ACAM,
author = {M. Sheinin and Y. Y. Schechner and K. N. Kutulakos},
title = {{Computational Imaging on the Electric Grid}},
journal = {Proc. IEEE CVPR},
year = {2017},

}

Data

DELIGHT is a Database of Electric LIGHTs. It contains bulb response functions and chromaticities, as described in our paper. Available for non-commercial use. You can use it if you clearly acknowledge the source by citing "Computational imaging on the electric grid" detailed above, in your work.

  1. The database DELIGHT described in the CVPR'17 paper Computational imaging on the electric grid.

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