When natural disasters occur, there is a possibility of having many injured people in the disaster area. In the meanwhile, rescue teams have to aid these injured individuals as fast as possible. In this study, we proposed a recognition system of individual status to help rescue teams. Employing Unmanned Aerial Vehicles (UAVs) system after disaster occurrence gives many advantages. For instance, a UAV can cover a wide area and provide aerial photographs in a short period. This study aims to classify whether an individual status is standing, sitting, or lying on the ground by using supervised machine learning. Experiments revealed that the system is able to recognize all three types of individual status with an accuracy of 95.6%. Moreover, the authors confirmed the usefulness of using a UAV to recognize individuals in the post-disaster scenario.