Improved object geo-location in airborne camera images using tight integration of vision and navigation data

A method for precise geo-location of objects that are observed by an airborne camera is described in this paper. The platform for image acquisition is a micro aerial vehicle (MAV) with an integrated navigation system. From the captured image sequences and MAV navigation data, the three-dimensional positions of objects of interest are retrieved. Different techniques for image feature tracking are compared. Combining measurements from multiple viewpoints in a Bundle Adjustment process yields optimal accuracy of the estimated object positions. The robustness of the optimization is enhanced by tight integration of data from both the vision and the navigation system.