A computer vision and control algorithm to follow a human target in a generic environment using a drone

This work proposes an innovative technique to solve the problem of tracking and following a generic human target by a drone in a natural, possibly dark scene. The algorithm does not rely on color information but mainly on shape information, using the HOG classifier, and on local brightness information, using the optical flow algorithm. We tried to keep the algorithm as light as possible, envisioning its future application on embedded or mobile devices. After several tests, performed modeling the system as a set of SISO feedback-controlled systems and calculating the Integral Squared Error as quality indicator, we noticed that the final performance, overall satisfactory, degrades as the background complexity and the presence of disturbance sources, such as sharp edges and moving objects that cross the target, increase .