  Egocentric cameras are being worn by an increasing number of users, among
them many security forces worldwide. GoPro cameras already penetrated the mass
market, reporting substantial increase in sales every year. As head-worn
cameras do not capture the photographer, it may seem that the anonymity of the
photographer is preserved even when the video is publicly distributed.
  We show that camera motion, as can be computed from the egocentric video,
provides unique identity information. The photographer can be reliably
recognized from a few seconds of video captured when walking. The proposed
method achieves more than 90% recognition accuracy in cases where the random
success rate is only 3%.
  Applications can include theft prevention by locking the camera when not worn
by its rightful owner. Searching video sharing services (e.g. YouTube) for
egocentric videos shot by a specific photographer may also become possible. An
important message in this paper is that photographers should be aware that
sharing egocentric video will compromise their anonymity, even when their face
is not visible.
