Compute-Efficient Geo-Localization of Targets from UAV Videos

Abstract

Unmanned Air Vehicles (UAVs) have crucial roles to play in traditional warfare, asymmetric conflicts, and also civilian applications such as search and rescue operations. Though satellites provide extensive coverage and capabilities crucial to many remote sensing tasks, UAVs have distinct edge over satellites in dynamic situations due to shorter revisit times and desired area/time coverage. The course, speed and altitude of a UAV can be dynamically altered, details of an activity of interest monitored by loitering over the area as desired. A fundamental requirement in most UAV operations is to find geo-coordinates of an object in the captured image. Most small, low-cost UAVs use low-cost, less accurate sensors. Matching with pre-registered images may not be possible in areas with low details or in emergency situations where terrain may have undergone severe sudden changes. In these situations that demand near real-time results and wider coverage, it is often enough to provide approximate results as long as bounds on accuracies can be established. Even when image registration is possible, it can benefit from these bounds to reduce search space thereby saving execution time. The prime contributions of this paper are computation of location of target anywhere in the image even at larger slant ranges, optimized algorithm to compute terrain elevation at target point, and use of visual simulation tool to validate the model. Analysis from simulation and results from real UAV flights are presented.