UAV application with moving human face detection and tracking

Unmanned aerial vehicles are small aircraft that are autonomous and/or remotely controlled by humans, which have been used in many areas such as civil, military and industry in recent years, and their usage areas are increasing day by day and are developing rapidly in terms of technology. There are many models of unmanned aerial vehicles. Four-engined models have advantages such as flight maneuvering features and ability to move in three axes. In this thesis study, human face detection and tracking application was carried out with a four-motor UAV. In this study, DJI Tello EDU Drone was used because it can be programmed with several different software languages, cheap cost, and material quality. The application was carried out in the PyCharm environment using the Python software language and OPENCV version 4.3.0 due to the availability of easy-to-learn and source studies. The human face detection and tracking process in the application was carried out using the OPENCV Library. For this process, first of all, real-time images were obtained from the fixed camera of the UAV. In this image obtained, the user decided and followed the process of whether there is a human face or not, without any selection process. Dependent factors were evaluated in order to obtain the desired results in indoor and outdoor flights. Thanks to these factors, the most suitable environments for the successful operation of the application were evaluated. As a result of this evaluation, indoor flights were chosen as the most suitable environment for this application. As a result, human face tracking application was carried out autonomously in this study.