Michael Raschke

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During eye tracking studies, vast amounts of spatio-temporal data in the form of eye gaze trajectories are recorded. Finding insights into these time-varying data sets is a challenging task. Visualization techniques such as heat maps or gaze plots help find patterns in the data but highly aggregate the data (heat maps) or are difficult to read due to(More)
The success of visualization techniques depends on their support of perceptual and cognitive processes to perceive the graphically represented information. Apart from measuring accuracy rates of correctly given answers and completion times in user studies, eye tracking experiments provide an additional technique to analyze perceptual and cognitive processes(More)
A key element for efficient video surveillance is situational awareness. Characteristics of human perception (e.g., inattentional blindness) as well as surveillance practice (e.g., CCTV operators have multiple responsibilities) often hinder comprehensive visual recognition of the activities in the monitored area. We support sit-uational awareness and reduce(More)
Eye tracking studies lead to spatio-temporal data in the form of gaze trajectories that show the behavior of gaze positions over time. Such data can be modeled as a dynamic graph that expresses the transitions of gaze positions between Areas of Interest (AOIs) by time-varying weighted relations. Moreover, a hierarchical organization of the AOIs may be of(More)