Newly evolving threats to public safety and security, related to attacks in public spaces, are catching the attention of both law enforcement and the general public. Such threats range from the emotional misbehaviour of sports fans in sports venues to well-planned terrorist attacks. Moreover, tools are needed to assist in the search for wanted persons. Static solutions, such as closed circuit television (CCTV), exist, but there is a need for a highly-portable, on-demand solution. Unmanned aerial vehicles (UAVs) have evolved drastically over the past decade. Developments are observed not only with regards to flight mechanisms and extended flight times but also in the imaging and image stabilization capabilities. Although different methods for facial recognition have existed for some time, dealing with imaging from a moving source to detect the faces in the crowd and compare them to an existing face database is a scientific problem that requires a complex solution. This paper deals with real-time face recognition in the crowd using unmanned aerial vehicles. Face recognition was performed using OpenCV and Dlib libraries.