This thesis outlines the development of a mathematical model which can be used to perform 3D reconstruction of a target object from surveillance images. 3D reconstruction is a common procedure in photogrammetry, but performing 3D reconstruction from surveillance images can be more difficult than typical photogrammetry applications. Surveillance images are generally captured in an unsystematic manner because there is no control over the target that is being photographed. Surveillance images can have a wide variety of fields of view, are often captured with uncalibrated cameras, and typically the targets are objects for which there is no other a priori information. For these reasons, performing 3D reconstruction from surveillance images may not be possible using standard photogrammetric methods, especially when the angular fields of view of the images are rather narrow.