Background subtraction is a common approach in computer vision to detect moving objects in video sequences taken with a static camera. Some background subtraction algorithms have been extended to support a pan/tilt camera but they are required to provide a background mosaic for motion estimation purposes. This thesis describes a system that avoids this requirement by separating the motion estimation system and background subtraction system into two separate modules. The first module performs motion compensation by employing a feature based image registration method and the RANSAC algorithm. The second module detects moving objects in rectified image frames using a background subtraction algorithm designed for a static camera. Three background subtraction algorithms were extended in the course of this project: mixture of Gaussians, non-parametric kernel density estimation and codebook. This thesis demonstrates the usefulness of separating of motion estimation from the background subtraction system as it allows us to extend any background subtraction algorithm designed for a static camera to support a pan/tilt camera. The detection results are presented for both indoor and outdoor video sequences taken with a pan/tilt camera.