  Due to their capability of acquiring aerial imagery, camera-equipped Unmanned
Aerial Vehicles (UAVs) are very cost-effective tools for acquiring traffic
information. However, not enough attention has been given to the validation of
the accuracy of these systems. In this paper, an analysis of the most
significant sources of error is done. This includes three key components.
First, a vehicle state estimation by means of statistical filtering. Second, a
quantification of the most significant sources of error. Third, a benchmark of
the estimated state compared with state-of-the-art reference sensors. This work
presents ways to minimize the errors of the most relevant sources. With these
error reductions, camera-equipped UAVs are very attractive tools for traffic
data acquisition. The test data and the source code are made publicly
available.
