  Motion segmentation is currently an active area of research in computer
Vision. The task of comparing different methods of motion segmentation is
complicated by the fact that researchers may use subtly different definitions
of the problem. Questions such as "Which objects are moving?", "What is
background?", and "How can we use motion of the camera to segment objects,
whether they are static or moving?" are clearly related to each other, but lead
to different algorithms, and imply different versions of the ground truth. This
report has two goals. The first is to offer a precise definition of motion
segmentation so that the intent of an algorithm is as well-defined as possible.
The second is to report on new versions of three previously existing data sets
that are compatible with this definition. We hope that this more detailed
definition, and the three data sets that go with it, will allow more meaningful
comparisons of certain motion segmentation methods.
