Computing That Serves

Robust Object Tracking: A Path-Planning Approach

Bryant Chandler's MS Thesis Defense

Monday, May 15th, 10:00 am

3350 TMCB – Conference Room

Advisor: Michael Goodrich



When attempting to follow ground-based moving objects (hereafter referred to as "waldos") using an unmanned air vehicle (UAV), occlusion can become a significant problem for computer vision algorithms designed to track the object. When a waldo is occluded, the computer vision algorithm loses the track and the UAV's ability to predict movement degrades. We propose a path-planning and replanning method that moves a UAV to a location that maximizes the important waldos that can be seen while accounting for occlusion, and attempts to maximize the area it can see during travel. The proposed work moves beyond state-of-the-art algorithms designed to follow a single waldo while accounting for occlusion to enable tracking multiple prioritized waldos.