Image-based aircraft pose estimation using moment invariants

The problem of estimating aircraft pose information from mono-ocular image data is considered using two different pose estimation algorithms. Both algorithms are based on the rotation invariant moment approach that was introduced by Dudani. The dependence of pose estimation accuracy on image resolution and aspect angle was investigated through simulations using sets of synthetic aircraft images. It is shown that increased pose-estimation accuracy can be obtained by breaking the nearest neighbour search procedure in two parts.