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AM-DCT: A Visual Attention Modeling Data Capturing Tool for Investigating Users' Interface Monitoring Behavior

Authors:

Sebastian Feuerstack,

Bertram WortelenAuthors Info & Claims

AVI '16: Proceedings of the International Working Conference on Advanced Visual Interfaces

Pages 252 - 255

https://doi.org/10.1145/2909132.2909276

Published: 07 June 2016 Publication History

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Abstract

Methods to get insights about users' monitoring behavior either depend on the expertise of Human Factor experts to model and predict stereotypic monitoring behavior or on performing eye tracking studies in simulated environments, which require subjects to be physically present and usually to be tested successively. AM-DCT is a tool that can be applied by domain experts without expertise in human factors and with limited training in parallel sessions to learn about a population's monitoring behavior. In an experiment 20 car drivers used the AM-DCT independently after watching a 15 minutes video tutorial. 19 subjects were able to model their monitoring behavior for a car overtaking scenario in 36 minutes on average. The identification of areas of interest for areas with clearly defined borders was very consistent among subjects. For those without clear borders an aggregated model of all participants seems surprisingly accurate to represent the real monitoring area.

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Cited By

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Green P(2024)Applying the SEEV Model to Assess Where People Will Look: Practical ConsiderationsProceedings of the Human Factors and Ergonomics Society Annual Meeting10.1177/1071181324127507468:1(566-571)Online publication date: 29-Aug-2024
https://doi.org/10.1177/10711813241275074

AM-DCT: A Visual Attention Modeling Data Capturing Tool for Investigating Users' Interface Monitoring Behavior
1. Human-centered computing

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Published In

AVI '16: Proceedings of the International Working Conference on Advanced Visual Interfaces

June 2016

400 pages

ISBN:9781450341318

DOI:10.1145/2909132

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Association for Computing Machinery

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Published: 07 June 2016

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AVI '16: International Working Conference on Advanced Visual Interfaces

June 7 - 10, 2016

Bari, Italy

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AVI '16 Paper Acceptance Rate 20 of 96 submissions, 21%;

Overall Acceptance Rate 128 of 490 submissions, 26%

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Green P(2024)Applying the SEEV Model to Assess Where People Will Look: Practical ConsiderationsProceedings of the Human Factors and Ergonomics Society Annual Meeting10.1177/1071181324127507468:1(566-571)Online publication date: 29-Aug-2024
https://doi.org/10.1177/10711813241275074

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