Paper Info
Title
Analyzing the Effect of Different Partial Overlap Sizes in Perceiving Visual Variables
Abstract
Element overlap in visualization techniques is a known problem, and high amounts of data and lack of available visual space potentialize this issue. Many studies have applied techniques to reduce occlusion levels in data visualizations, such as random jitter, element transparency, layout rearrangement, and focus+context techniques. However, few studies focus on the presence of occlusion, which is a relevant topic for visualizations where some degree of overlap is inevitable or purposefully explored. This paper takes a step in this direction, and presents a comparative study of visual variables, measuring their robustness to overlap and number of unique values. The study used a grid layout to display visual variables (hue, saturation, shape, text, orientation, and texture), and varied percentage of occlusion (0%, 50%, 60% and 70%) and number of unique values (3, 4 and 5) to measure the effect they cause on the speed and accuracy to locate the visual variables. Hence, 48 volunteers performed locate tasks on a tool that automatically generate a grid of visual variables and collect their answers. The results revealed that hue and shape were robust to high occlusion levels and a high number of unique values. Text and texture had medium loss of performance, while saturation and orientation were the most negatively affected.
Year
DOI
Venue
2019
10.1109/IV.2019.00016
2019 23rd International Conference Information Visualisation (IV)
Keywords
DocType
ISSN
evaluation, visual variables, overlap, occlusion
Conference
1550-6037
ISBN
Citations 
PageRank 
978-1-7281-2839-9
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Diego Hortencio dos Santos100.68
Anderson Gregorio Marques Soares200.34
Rodrigo Santos Do Amor Divino Lima303.38
Elvis Thermo Carvalho Miranda400.34
Carlos Gustavo Resque dos Santos526.46
Bianchi Serique Meiguins65628.03