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Activity Number:
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67
- Section on Statistical Computing: Data Science
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Type:
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Contributed
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Date/Time:
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Monday, August 3, 2020 : 10:00 AM to 2:00 PM
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Sponsor:
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Section on Statistical Computing
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Abstract #312439
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Title:
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Defining Areas of Interest for Eye-Tracking Data: Implementing a Systematic Approach
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Author(s):
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Joanna Coltrin* and Eric McKinney and Breanna Studenka and Juergen Symanzik
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Companies:
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Utah State University and Utah State University and Utah State University and Utah State University
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Keywords:
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USU Posture Study;
Voronoi Tessellation Method;
Data Visualization
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Abstract:
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There exists a variety of methods that have been used to analyze eye-tracking data. One of the general methods involves the use of Areas of Interest (AOIs). AOIs are predefined areas of an image used to determine characteristics of eye-tracking data. While most AOIs are defined by hand, we discuss the use of systematic AOIs and the application of the systematic Voronoi Tessellation Method. Differentiated eye-tracking data can then be compared within the AOIs to determine whether subjects from a treatment group looked at the images differently than subjects from a control group and where those differences occurred.
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Authors who are presenting talks have a * after their name.
