Utilization of Uav-Borne Rgb Data For Monitoring Horses: Comparison of Classification Methods

The paper describes utilization of remotely sensed RGB data to support routine monitoring horses in natural environment on demand. Data are sensed using an unmanned aerial vehicle (UAV). UAVs provide very high spatial resolution data sensed at a low altitude on demand. Sensing is limited by weather conditions and legal rules only. Terrain does not need to be accessible. The paper provides comparison of several pixel-based and object-based classification methods, namely Maximum Likelihood, Random Trees, SVM, and K-NN. Manual classification is used as a reference method.