As the market for unmanned air vehicles (UAVs) rapidly expands, the need for algorithmsthat improve the capabilities of those vehicles is also growing. One valuable capability for UAVsis that of persistent tracking—the ability to find and track another moving object, usually on theground, from an aerial platform. This thesis presents a method for tracking multiple ground targetsfrom an airborne camera. Moving objects on the ground are detected by using frame-to-frameregistration. The detected objects are then tracked using the newly developed recursive RANSACalgorithm. Much video tracking work has focused on using appearance-based processing for tracking,with some approaches using dynamic trackers such as Kalman filters. This work demonstratesa fusion of computer vision and dynamic tracking to increase the ability of an unmanned air platformto identify and robustly track moving targets. With a C++ implementation of the algorithmsrunning on the open source Robot Operating System (ROS) framework, the system developed iscapable of processing 1920x1080 resolution video at over seven frames per second on a desktopcomputer.
College and Department
Ira A. Fulton College of Engineering and Technology; Electrical and Computer Engineering
BYU ScholarsArchive Citation
DeFranco, Patrick, "Detecting and Tracking Moving Objects from a Small Unmanned Air Vehicle" (2015). Theses and Dissertations. 5311.
unmanned air vehicle, recursive RANSAC, RANSAC, multiple target tracking, computer, vision, homography