  Unobtrusive monitoring of distances between people indoors is a useful tool
in the fight against pandemics. A natural resource to accomplish this are
surveillance cameras. Unlike previous distance estimation methods, we use a
single, overhead, fisheye camera with wide area coverage and propose two
approaches. One method leverages a geometric model of the fisheye lens, whereas
the other method uses a neural network to predict the 3D-world distance from
people-locations in a fisheye image. To evaluate our algorithms, we collected a
first-of-its-kind dataset using single fisheye camera, that comprises a wide
range of distances between people (1-58 ft) and will be made publicly
available. The algorithms achieve 1-2 ft distance error and over 95% accuracy
in detecting social-distance violations.
