Graph drawing by force-directed placement
Software—Practice & Experience
User Studies: Why, How, and When?
IEEE Computer Graphics and Applications
Attention-based design of augmented reality interfaces
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Saliency-guided Enhancement for Volume Visualization
IEEE Transactions on Visualization and Computer Graphics
DOTS: support for effective video surveillance
Proceedings of the 15th international conference on Multimedia
Journal of Management Information Systems
Mediated attention with multimodal augmented reality
Proceedings of the 2009 international conference on Multimodal interfaces
Multimedia Analysis + Visual Analytics = Multimedia Analytics
IEEE Computer Graphics and Applications
Continuous tracking within and across camera streams
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Directing attention and influencing memory with visual saliency modulation
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
IEEE Transactions on Visualization and Computer Graphics
Attention and Visual Memory in Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
State of the Art Report on Video-Based Graphics and Video Visualization
Computer Graphics Forum
Intelligent Network Video: Understanding Modern Video Surveillance Systems, Second Edition
Intelligent Network Video: Understanding Modern Video Surveillance Systems, Second Edition
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We investigate four different variants of attention-guiding video visualization techniques that aim to help users distribute their attention equally among potential objects of interest: bounding box visualization, force-directed visualization, top-down visualization, grid visualization. Objects of interest are highlighted by rectangular shapes and then we concentrate on the manipulation of color, motion, and size. We conducted a controlled laboratory user study (n=25) to compare the four visualization techniques and the unmodified video material as baseline. We evaluated task performance and distribution of attention in a search task. These two properties become especially important when video material with numerous objects has to be observed. The distribution of attention was measured by eye tracking. Our results show that a more even distribution of attention between the objects can be achieved by attention-guiding visualization, compared to unmodified video. Many participants feel more comfortable when they look at bounding boxes and the grid, but improvements in search task performance could not be confirmed.