Incremental Mosaicking of Images from Autonomous, Small-Scale UAVs

Unmanned aerial vehicles (UAVs) have been recently deployed in various civilian applications such as environmental monitoring, aerial imaging or surveillance. Small-scale UAVs are of special interest for first responders since they can rather easily provide bird´s eye view images of disaster areas. In this paper we present a hybrid approach to mosaick an overview image of the area of interest given a set of individual images captured by UAVs flying at low altitude. Our approach combines metadata-based and imagebased stitching methods in order to overcome the challenges of low-altitude, small-scale UAV deployment such as nonnadir view, inaccurate sensor data, non-planar ground surfaces and limited computing and communication resources. For the generation of the overview image we preserve georeferencing as much as possible, since this is an important requirement for disaster management applications. Our mosaicking method has been implemented on our UAV system and evaluated based on a quality metric.