  We introduce a simple and effective method for retrieval of videos showing a
specific event, even when the videos of that event were captured from
significantly different viewpoints. Appearance-based methods fail in such
cases, as appearances change with large changes of viewpoints.
  Our method is based on a pixel-based feature, "motion barcode", which records
the existence/non-existence of motion as a function of time. While appearance,
motion magnitude, and motion direction can vary greatly between disparate
viewpoints, the existence of motion is viewpoint invariant. Based on the motion
barcode, a similarity measure is developed for videos of the same event taken
from very different viewpoints. This measure is robust to occlusions common
under different viewpoints, and can be computed efficiently.
  Event retrieval is demonstrated using challenging videos from stationary and
hand held cameras.
