Kalman filtering of pose estimates in applications of the RAPID video rate tracker

RAPID is a video-rate model based tracker which generates refined estimates of an object's position and orientation (pose) given approximate initial estimates. A practical application of this technique requires (1) prediction from-frame-to-frame of the pose of the object being tracked, to accommodate realistic target movement and (2) temporal integration of pose estimates to reduce measurement noise. These needs are both satisfied by a Kalman filter. In order to apply a Kalman filter, however, we first construct statistical models of both the apparent motion of the object between frames and also of the accuracy of pose measurements made at each processed frame. The filtered tracker output provides a robust estimate of object pose at video rate when implemented in software running on a standard mini-computer. The capabilities of this technique are demonstrated by application to the task of monitoring the pose of an unmanned aircraft during its approach to an airfield and during landing.