Tracking a person with pre-recorded image database and a pan, tilt, and zoom camera

This paper proposes a novel tracking strategy that can robustly track a person or other object, within a fixed environment using a pan, tilt, and zoom camera with the help of a pre-recorded image database. We define a set called the minimum camera parameter settings (MCPS) which contains just enough camera states as required to survey the environment for the target. This set of states is used to facilitate tracking and segmentation. The idea is to store a background image of the environment for every camera state in MCPS, thus creating an image database. During tracking camera movements are restricted to states in MCPS (or a version of this set that is augmented to improve smoothness of tracking). Scanning for the target and segmentation of the target from the background are simplified as each current image can be compared with the corresponding pre-recorded background image.