Robust Registration and Filtering for Moving Object Detection in Aerial Videos

In this paper we present a multi-frame motion detection approach for aerial platforms with a two-folded contribution. First, we propose a novel image registration method, which can robustly cope with a large variety of aerial imagery. We show that it can benefit from a hardware accelerated implementation using graphic cards, allowing processing at high frame rate. Second, to handle the inaccuracy of the registration and sensor noise that result in false-alarms, we present an efficient filtering step to reduce incorrect motion hypotheses that arise from background substraction. We show that the proposed filtering significantly improves the precision of the motion detection while maintaining high recall. We introduce a new dataset for evaluating aerial surveillance systems, which will be made available for comparison. We evaluate the registration performance in terms of accuracy and speed as well as the filtering in terms of motion detection performance.