Discrimination and tracking of dismounts using low-resolution aerial video sequences

In this paper, we address the problem of robust detection of dismounts from low-resolution video data sequences. We outline a methodology based on SSCI's ultra-fast image alignment algorithm, and a combination of static and kinematic features for dismount detection. We perform the dismount detection classification using a learning classifier algorithm. Our results are promising and very valuable for low-resolution imagery where previous techniques for dismount detection such as SURF and SIFT features do not perform very well.