  We present a novel approach to optimally retarget videos for varied displays
with differing aspect ratios by preserving salient scene content discovered via
eye tracking. Our algorithm performs editing with cut, pan and zoom operations
by optimizing the path of a cropping window within the original video while
seeking to (i) preserve salient regions, and (ii) adhere to the principles of
cinematography. Our approach is (a) content agnostic as the same methodology is
employed to re-edit a wide-angle video recording or a close-up movie sequence
captured with a static or moving camera, and (b) independent of video length
and can in principle re-edit an entire movie in one shot. Our algorithm
consists of two steps. The first step employs gaze transition cues to detect
time stamps where new cuts are to be introduced in the original video via
dynamic programming. A subsequent step optimizes the cropping window path (to
create pan and zoom effects), while accounting for the original and new cuts.
The cropping window path is designed to include maximum gaze information, and
is composed of piecewise constant, linear and parabolic segments. It is
obtained via L(1) regularized convex optimization which ensures a smooth
viewing experience. We test our approach on a wide variety of videos and
demonstrate significant improvement over the state-of-the-art, both in terms of
computational complexity and qualitative aspects. A study performed with 16
users confirms that our approach results in a superior viewing experience as
compared to gaze driven re-editing and letterboxing methods, especially for
wide-angle static camera recordings.
