Coordinating spatial referencing using shared gaze

2010 ◽  
Vol 17 (5) ◽  
pp. 718-724 ◽  
Author(s):  
Mark B. Neider ◽  
Xin Chen ◽  
Christopher A. Dickinson ◽  
Susan E. Brennan ◽  
Gregory J. Zelinsky
2020 ◽  
Vol 4 (CSCW2) ◽  
pp. 1-25
Author(s):  
Grete Helena Kütt ◽  
Teerapaun Tanprasert ◽  
Jay Rodolitz ◽  
Bernardo Moyza ◽  
Samuel So ◽  
...  
Keyword(s):  

Author(s):  
Sarah D’Angelo ◽  
Bertrand Schneider

Abstract The past decade has witnessed a growing interest for using dual eye tracking to understand and support remote collaboration, especially with studies that have established the benefits of displaying gaze information for small groups. While this line of work is promising, we lack a consistent framework that researchers can use to organize and categorize studies on the effect of shared gaze on social interactions. There exists a wide variety of terminology and methods for describing attentional alignment; researchers have used diverse techniques for designing gaze visualizations. The settings studied range from real-time peer collaboration to asynchronous viewing of eye-tracking video of an expert providing explanations. There has not been a conscious effort to synthesize and understand how these different approaches, techniques and applications impact the effectiveness of shared gaze visualizations (SGVs). In this paper, we summarize the related literature and the benefits of SGVs for collaboration, describe important terminology as well as appropriate measures for the dual eye-tracking space and discuss promising directions for future research. As eye-tracking technology becomes more ubiquitous, there is pressing need to develop a consistent approach to evaluation and design of SGVs. The present paper makes a first and significant step in this direction.


2010 ◽  
Vol 8 (6) ◽  
pp. 1084-1084 ◽  
Author(s):  
M. Neider ◽  
M. W. Voss ◽  
A. F. Kramer

2021 ◽  
Author(s):  
Kalamkas Yessimkhanova ◽  
Mátyás Gede

<p>The majority of studies are dedicated to the analysis of climate change and climate models with no regard for data visualization part. Therefore, this research is aimed at highlighting challenges, with an emphasis on spatial referencing that can occur while visualizing CORDEX data. CORDEX data are stored in NetCDF file format, and sometimes georeferencing may be misconceived in QGIS software. For this reason, two techniques of georeferencing data are examined in this work. The first way of data georeferencing is re-projecting coordinates from original projection to an interpolated latitude/longitude grid. The second way is re-encrypting initial data file so that QGIS is able to interpret projection information. Preference of using QGIS explained by two reasons: it is open source GIS application and it has expanded visualization toolkit.</p><p>In addition, there are a great deal of climate models based on CORDEX data for some regions whereas there is a lack of climate projections for particular areas. In this regard, carrying out analysis for the region of Kazakhstan is beneficial. Outcomes of this research may stimulate spreading local climate models for Kazakhstan territory. Results are represented in the form of maps of Kazakhstan illustrating temperature change over 21<sup>st</sup> century time period.</p>


2020 ◽  
Vol 44 (6) ◽  
Author(s):  
Andrea Bender ◽  
Sarah Teige‐Mocigemba ◽  
Annelie Rothe‐Wulf ◽  
Miriam Seel ◽  
Sieghard Beller
Keyword(s):  

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