Efficient Camera Control using 2D Visual Information for Unmanned Aerial Vehicle-based Cinematography
Nikolaos Passalis, Anastasios Tefas, Ioannis Pitas · 2018
Using Unmanned Aerial Vehicles (UAVs), also known as drones, for covering public sport events, such as bicycle races, is becoming increasingly popular. Even though the problem of controlling the flight path of a drone is well studied in the literature, little work has been done on controlling the shooting camera for producing professional grade video footage. In this work we propose a fast and efficient proportional-integral-derivative (PID) based control algorithm that rely solely on 2D visual information and we demonstrate that it is possible to accurately control the camera without inferring the 3D position of the target. To ensure that the proposed method will not exhibit undesired behavior, a genetic algorithm is used to tune its parameters using a properly defined fitness function. The proposed method is evaluated using two datasets that contain actual drone footage: a dataset that contains videos of a single cyclist, and a dataset that contains actually footage from a bicycle race event, the Giro D'Italia bicycle race.