bezarios et al.

Estimation.bib

@@ -1,15 +1,31 @@
-@inproceedings{redmondVisualCuesEstimation2019b,
+@article{bezerianosPerceptionVisualVariables2012,
+  title = {Perception of {{Visual Variables}} on {{Tiled Wall-Sized Displays}} for {{Information Visualization Applications}}},
+  author = {Bezerianos, Anastasia and Isenberg, Petra},
+  year = {2012},
+  month = dec,
+  journal = {IEEE Transactions on Visualization and Computer Graphics},
+  volume = {18},
+  number = {12},
+  pages = {2516--2525},
+  issn = {1941-0506},
+  doi = {10.1109/TVCG.2012.251},
+  urldate = {2024-03-05},
+  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.},
+  keywords = {Data visualization,Information analysis,Information visualization,Navigation,perception,Visual analytics,wall-displays},
+  file = {/Users/cbbcbail/Zotero/storage/DBDPJGWU/Bezerianos and Isenberg - 2012 - Perception of Visual Variables on Tiled Wall-Sized.pdf;/Users/cbbcbail/Zotero/storage/F3F9BKZR/6327257.html}
+}
+
+@inproceedings{redmondVisualCuesEstimation2019,
   title = {Visual {{Cues}} in {{Estimation}} of {{Part-To-Whole Comparisons}}},
   booktitle = {2019 {{IEEE Visualization Conference}} ({{VIS}})},
   author = {Redmond, Stephen},
   year = {2019},
   month = oct,
   pages = {1--5},
   doi = {10.1109/VISUAL.2019.8933718},
-  urldate = {2024-03-04},
+  urldate = {2024-01-18},
   abstract = {Pie charts were first published in 1801 by William Playfair and have caused some controversy since. Despite the suggestions of many experts against their use, several empirical studies have shown that pie charts are at least as good as alternatives. From Brinton to Few on one side and Eells to Kosara on the other, there appears to have been a hundred-year war waged on the humble pie. In this paper a set of experiments are reported that compare the performance of pie charts and horizontal bar charts with various visual cues. Amazon's Mechanical Turk service was employed to perform the tasks of estimating segments in various part-to-whole charts. The results lead to recommendations for data visualization professionals in developing dashboards.},
-  keywords = {Bars,Data visualization,Empirical studies in visualization,Estimation,Human computer interaction,Human-centered computing,Indexes,Task analysis,Visualization,Visualization design and evaluation methods},
-  file = {/Users/cbbcbail/Zotero/storage/TP8HB55J/Redmond - 2019 - Visual Cues in Estimation of Part-To-Whole Compari.pdf}
+  file = {/Users/cbbcbail/Zotero/storage/TLT5P9KU/Redmond - 2019 - Visual Cues in Estimation of Part-To-Whole Compari.pdf;/Users/cbbcbail/Zotero/storage/WKVHF2A9/8933718.html}
 }
 
 @article{rubio-sanchezAxisCalibrationImproving2014,
@@ -53,7 +69,7 @@ @article{ventocillaComparativeUserStudy2020
   volume = {19},
   number = {4},
   pages = {318--338},
-  publisher = {{SAGE Publications}},
+  publisher = {SAGE Publications},
   issn = {1473-8716},
   doi = {10.1177/1473871620922166},
   urldate = {2024-03-04},

estimation.md

@@ -7,6 +7,10 @@ csl: ieee.csl
 
 # Studies on Estimation in Visualization
 
+* Two user studies conducting perception estimation tasks of visual variables on tiled, high-resolution wall-sized displays. The authors compare estimation error for various viewing distances, angles, and sizes in both fixed position and free movement studies. The results show that performance was best when the information was in full view despite being farther away or with smaller objects to compare. viewing distance affected area and angle estimations but not length, and lower locations performed differently than other locations. Allowing subjects to have free movement increased time but did not provide meaningful accuracy improvements. 
+
+    [@bezerianosPerceptionVisualVariables2012]
+
 * Motivated by exploratory, overview stages of data analysis, the authors propose a method to allow for estimation of data values in radial axis charts (e.g. star coordinates and RadVis) where data is inevitably lost during the transformation. Calibrating (labelling) and centering data in star coordinate plots considerably increases attribute estimation accuracy.
 
     [@rubio-sanchezAxisCalibrationImproving2014]