Literature DB >> 26357198

Visual Analytics Methodology for Eye Movement Studies.

G Andrienko1, N Andrienko, M Burch, D Weiskopf.   

Abstract

Eye movement analysis is gaining popularity as a tool for evaluation of visual displays and interfaces. However, the existing methods and tools for analyzing eye movements and scanpaths are limited in terms of the tasks they can support and effectiveness for large data and data with high variation. We have performed an extensive empirical evaluation of a broad range of visual analytics methods used in analysis of geographic movement data. The methods have been tested for the applicability to eye tracking data and the capability to extract useful knowledge about users' viewing behaviors. This allowed us to select the suitable methods and match them to possible analysis tasks they can support. The paper describes how the methods work in application to eye tracking data and provides guidelines for method selection depending on the analysis tasks.

Mesh:

Year:  2012        PMID: 26357198     DOI: 10.1109/TVCG.2012.276

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  7 in total

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Review 3.  Analysis and visualisation of movement: an interdisciplinary review.

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5.  Epistemic Network Analyses of Economics Students' Graph Understanding: An Eye-Tracking Study.

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6.  Gaze-driven placement of items for proactive visual exploration.

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Journal:  J Vis (Tokyo)       Date:  2021-11-11       Impact factor: 1.974

Review 7.  Eye-Tracking Feature Extraction for Biometric Machine Learning.

Authors:  Jia Zheng Lim; James Mountstephens; Jason Teo
Journal:  Front Neurorobot       Date:  2022-02-01       Impact factor: 2.650

  7 in total

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