In this paper, we address the issue of tracking moving objects in an environment covered
by multiple uncalibrated cameras with overlapping fields of view, typical of most surveillance
setups. In such a scenario, it is essential to establish correspondence between tracks of the same
object, seen in different cameras, to recover complete information about the object. We call
this the problem of consistent labeling of objects when seen in multiple cameras. We employ
a novel approach of finding the limits of field of view (FOV) of each camera as visible in the
other cameras. We show that if the FOV lines are known, it is possible to disambiguate between
multiple possibilities for correspondence. We present a method to automatically recover these
lines by observing motion in the environment. Furthermore, once these lines are initialized, the
homography between the views can also be recovered. We present results on indoor and outdoor
sequences, containing persons and vehicles.
