Title
Perception of Visual Variables on Tiled Wall-Sized Displays for Information Visualization Applications
Abstract
We present the results of two user studies on the perception of visual variables on tiled high-resolution wall-sized displays. We contribute an understanding of, and indicators predicting how, large variations in viewing distances and viewing angles affect the accurate perception of angles, areas, and lengths. Our work, thus, helps visualization researchers with design considerations on how to create effective visualizations for these spaces. The first study showed that perception accuracy was impacted most when viewers were close to the wall but differently for each variable (Angle, Area, Length). Our second study examined the effect of perception when participants could move freely compared to when they had a static viewpoint. We found that a far but static viewpoint was as accurate but less time consuming than one that included free motion. Based on our findings, we recommend encouraging viewers to stand further back from the display when conducting perception estimation tasks. If tasks need to be conducted close to the wall display, important information should be placed directly in front of the viewer or above, and viewers should be provided with an estimation of the distortion effects predicted by our work—or encouraged to physically navigate the wall in specific ways to reduce judgement error.
Year
DOI
Venue
2012
10.1109/TVCG.2012.251
IEEE Trans. Vis. Comput. Graph.
Keywords
Field
DocType
colour displays,colour graphics,computer displays,data visualisation,human factors,visual perception,angles perception,areas perception,distortion effect estimation,free motion,information visualization applications,lengths perception,perception accuracy,perception estimation tasks,static viewpoint,tiled high-resolution wall-sized displays,visual variables perception,visualization design,Information visualization,perception,wall-displays
Computer vision,Data visualization,Information visualization,Computer science,Visualization,Visual analytics,Artificial intelligence,Distortion,Perception,User studies,Visual perception
Journal
Volume
Issue
ISSN
18
12
1077-2626
Citations 
PageRank 
References 
41
1.12
24
Authors
2
Name
Order
Citations
PageRank
Anastasia Bezerianos167437.75
Petra Isenberg2147168.00