Deep Learning-Based Real-Time Multiple-Object Detection and Tracking via Drone

Target tracking has been one of the many popular applications that an unmanned aerial vehicle (UAV) is used for, in a variety of missions from intelligence gathering and surveillance to reconnaissance missions. Target tracking by autonomous vehicles could prove to be a beneficial tool for the development of guidance systems- Pedestrian detection, dynamic vehicle detection, and obstacle detection too and can improve the features of the guiding assistance system. An aerial vehicle equipped with object recognition and tracking features could play a vital role in drone navigation and obstacle avoidance; video surveillance, aerial view for traffic management, self-driving systems, surveillance of road conditions, and emergency response too. Target detection capacity in drones has made stupendous progress off late. Earlier, target detection in drone systems mostly used vision-based target finding algorithms.