Interaction with dynamic image content is challenging for user perception, cognition and motor action. This dissertation identifies appropriate gaze-based interaction techniques for moving object selection in image sequences using multiple cross-sectional and one longitudinal user study. Further investigations evaluate how gaze-based interaction and automated image exploitation algorithms support human video exploitation as well as whether gaze-based user task classification is feasible
