Literature DB >> 12564561

3-D eye movement analysis.

Andrew Duchowski1, Eric Medlin, Nathan Cournia, Hunter Murphy, Anand Gramopadhye, Santosh Nair, Jeenal Vorah, Brian Melloy.   

Abstract

This paper presents a novel three-dimensional (3-D) eye movement analysis algorithm for binocular eye tracking within virtual reality (VR). The user's gaze direction, head position, and orientation are tracked in order to allow recording of the user's fixations within the environment. Although the linear signal analysis approach is itself not new, its application to eye movement analysis in three dimensions advances traditional two-dimensional approaches, since it takes into account the six degrees of freedom of head movements and is resolution independent. Results indicate that the 3-D eye movement analysis algorithm can successfully be used for analysis of visual process measures in VR. Process measures not only can corroborate performance measures, but also can lead to discoveries of the reasons for performance improvements. In particular, analysis of users' eye movements in VR can potentially lead to further insights into the underlying cognitive processes of VR subjects.

Mesh:

Year:  2002        PMID: 12564561     DOI: 10.3758/bf03195486

Source DB:  PubMed          Journal:  Behav Res Methods Instrum Comput        ISSN: 0743-3808


  12 in total

1.  Real-time recording and classification of eye movements in an immersive virtual environment.

Authors:  Gabriel Diaz; Joseph Cooper; Dmitry Kit; Mary Hayhoe
Journal:  J Vis       Date:  2013-10-10       Impact factor: 2.240

2.  Memory and prediction in natural gaze control.

Authors:  Gabriel Diaz; Joseph Cooper; Mary Hayhoe
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2013-09-09       Impact factor: 6.237

3.  Saccades to future ball location reveal memory-based prediction in a virtual-reality interception task.

Authors:  Gabriel Diaz; Joseph Cooper; Constantin Rothkopf; Mary Hayhoe
Journal:  J Vis       Date:  2013-01-16       Impact factor: 2.240

4.  GazeMetrics: An Open-Source Tool for Measuring the Data Quality of HMD-based Eye Trackers.

Authors:  Isayas B Adhanom; Samantha C Lee; Eelke Folmer; Paul MacNeilage
Journal:  Proc Eye Track Res Appl Symp       Date:  2020-06

5.  Eye tracking cognitive load using pupil diameter and microsaccades with fixed gaze.

Authors:  Krzysztof Krejtz; Andrew T Duchowski; Anna Niedzielska; Cezary Biele; Izabela Krejtz
Journal:  PLoS One       Date:  2018-09-14       Impact factor: 3.240

6.  Eye-tracking Analysis of Interactive 3D Geovisualization.

Authors:  Lukas Herman; Stanislav Popelka; Vendula Hejlova
Journal:  J Eye Mov Res       Date:  2017-05-31       Impact factor: 0.957

7.  Development and Calibration of an Eye-Tracking Fixation Identification Algorithm for Immersive Virtual Reality.

Authors:  Jose Llanes-Jurado; Javier Marín-Morales; Jaime Guixeres; Mariano Alcañiz
Journal:  Sensors (Basel)       Date:  2020-09-01       Impact factor: 3.576

8.  MAD saccade: statistically robust saccade threshold estimation via the median absolute deviation.

Authors:  Benjamin Voloh; Marcus R Watson; Seth König; Thilo Womelsdorf
Journal:  J Eye Mov Res       Date:  2020-05-12       Impact factor: 0.957

9.  Pupillary and Microsaccadic Responses to Cognitive Effort and Emotional Arousal During Complex Decision Making.

Authors:  Krzysztof Krejtz; Justyna Żurawska; Andrew T Duchowski; Szymon Wichary
Journal:  J Eye Mov Res       Date:  2020-05-17       Impact factor: 0.957

10.  ARETT: Augmented Reality Eye Tracking Toolkit for Head Mounted Displays.

Authors:  Sebastian Kapp; Michael Barz; Sergey Mukhametov; Daniel Sonntag; Jochen Kuhn
Journal:  Sensors (Basel)       Date:  2021-03-23       Impact factor: 3.576

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