An independent moving objection detection system is described which uses a colour background model for a nonstationary sensor. Over time the RGB distribution of a static point in a scene, observed from a static or moving camera, is cylindrical rather than spherical and is modelled as such. The background model is recursively updated over time and is robustly aligned to the most recent frame. Discrepancies between the current observed frame and the background model are considered foreground events and are determined using a classification framework which combines per-pixel colour and brightness differences. In principle the colour (RGB) images provide greater discriminative power than greyscale (brightness). However for several sequences tested, which are of road scenes from an airborne sensor, it was found that the colour information did not improve the classification of foreground pixels significantly.