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Evaluation of Attention‐Guiding Video Visualization
Author(s) -
Kurzhals K.,
Höferlin M.,
Weiskopf D.
Publication year - 2013
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.12092
Subject(s) - visualization , computer science , grid , task (project management) , eye tracking , minimum bounding box , computer vision , bounding overwatch , computer graphics (images) , visual search , video tracking , information visualization , artificial intelligence , human–computer interaction , video processing , mathematics , geometry , management , economics , image (mathematics)
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.