Detection Thresholds for Label Motion in Visually Cluttered Displays

While label placement algorithms are generally successful in managing visual clutter by preventing label overlap, they can also cause significant label movement in dynamic displays. This study investigates motion detection thresholds for various types of label movement in realistic and complex virtual environments, which can be helpful for designing less salient and disturbing algorithms. Our results show that label movement in stereoscopic depth is shown to be less noticeable than similar lateral monoscopic movement, inherent to 2D label placement algorithms. Furthermore, label movement can be introduced more readily into the visual periphery (over 15 degrees eccentricity) because of reduced sensitivity in this region. Moreover, under the realistic viewing conditions that we used, motion of isolated labels is more easily detected than that of overlapping labels. This perhaps counterintuitive finding may be explained by visual masking due to the visual clutter arising from the label overlap. The quantitative description of the findings presented in this paper should be useful not only for label placement applications, but also for any cluttered AR or VR application in which designers wish to control the users' visual attention, either making text labels more or less noticeable as needed.