<title>Automatic 3D object pose estimation in IR image sequences for forward motion applications</title>

The successful mission of autonomous airborne systems like unmanned aerial vehicles (UAV) strongly depends on the performance of automatic image processing used for navigation, target acquisition and terminal homing. In this paper we propose a method for automatic determination of missile position and orientation (pose) during target approach. The flight path is characterized by a forward motion, i.e. an approximately linear motion along the optical axis of the sensor system. Due to the lack of disparity, classical methods based on stereo triangulation are not suitable for 3D object recognition. To handle this we applied the SoftPOSIT algorithm, originally proposed by D. DeMenthon, and adapted it to fit our specific needs: The gathering of image points is done by multi-threshold segmentation, texture analysis, 2D tracking and edge detection. The reference points are updated in each loop and the calculated pose is smoothed using the quaternion representation of the model’s orientation in order to stabilize the computations. We will show some results of image based determination of trajectories for airborne systems. Terminal homing is demonstrated by tracking the 3D pose of a vehicle in an image sequence taken in oblique view and gathered by an infrared sensor mounted to a helicopter.