Foveated Video Object Detection

Humans are still unsurpassed in their ability to search for objects in visual scenes. On the other hand, object detection continues to be one of the hot areas of computer vision, and it attests both to the fundamental importance of the problem and the fact that existing state-of-the-art algorithms are still shy of performing well in practice. We propose to utilizes human vision modeling of a foveated view along with saccadic movements of the eye to quickly and accurately find and track objects of interest. We will develop a framework that combines state-of-the-art commercial grade video object detection system with foveated visual field and saccade fixation point modeling for better and faster object detection in UAS video feeds.