  In recent years, the technological improvements of low-cost small-scale
Unmanned Aerial Vehicles (UAVs) are promoting an ever-increasing use of them in
different tasks. In particular, the use of small-scale UAVs is useful in all
these low-altitude tasks in which common UAVs cannot be adopted, such as
recurrent comprehensive view of wide environments, frequent monitoring of
military areas, real-time classification of static and moving entities (e.g.,
people, cars, etc.). These tasks can be supported by mosaicking and change
detection algorithms achieved at low-altitude. Currently, public datasets for
testing these algorithms are not available. This paper presents the UMCD
dataset, the first collection of geo-referenced video sequences acquired at
low-altitude for mosaicking and change detection purposes. Five reference
scenarios are also reported.
