  We present a novel object tracking scheme that can track rigid objects in
real time. The approach uses subpixel-precise image edges to track objects with
high accuracy. It can determine the object position, scale, and rotation with
subpixel-precision at around 80fps. The tracker returns a reliable score for
each frame and is capable of self diagnosing a tracking failure. Furthermore,
the choice of the similarity measure makes the approach inherently robust
against occlusion, clutter, and nonlinear illumination changes. We evaluate the
method on sequences from rigid objects from the OTB-2015 and VOT2016 dataset
and discuss its performance. The evaluation shows that the tracker is more
accurate than state-of-the-art real-time trackers while being equally robust.
