  Handling object interaction is a fundamental challenge in practical
multi-object tracking, even for simple interactive effects such as one object
temporarily occluding another. We formalize the problem of occlusion in
tracking with two different abstractions. In object-wise occlusion, objects
that are occluded by other objects do not generate measurements. In
measurement-wise occlusion, a previously unstudied approach, all objects may
generate measurements but some measurements may be occluded by others. While
the relative validity of each abstraction depends on the situation and sensor,
measurement-wise occlusion fits into probabilistic multi-object tracking
algorithms with much looser assumptions on object interaction. Its value is
demonstrated by showing that it naturally derives a popular approximation for
lidar tracking, and by an example of visual tracking in image space.
