  Road traffic scene reconstruction from videos has been desirable by road
safety regulators, city planners, researchers, and autonomous driving
technology developers. However, it is expensive and unnecessary to cover every
mile of the road with cameras mounted on the road infrastructure. This paper
presents a method that can process aerial videos to vehicle trajectory data so
that a traffic scene can be automatically reconstructed and accurately
re-simulated using computers. On average, the vehicle localization error is
about 0.1 m to 0.3 m using a consumer-grade drone flying at 120 meters. This
project also compiles a dataset of 50 reconstructed road traffic scenes from
about 100 hours of aerial videos to enable various downstream traffic analysis
applications and facilitate further road traffic related research. The dataset
is available at https://github.com/duolu/CAROM.
