A 3D Model of the Mosque 2 at Kua Ruins (Model 2 of 3) Dahkki Heinz Rüther (6040169)

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Fleshed Networks: Exhibition Documentation (2025), WebXR Experience on the STYLY Platform for <i>Constellations</i>, ISEA (International Symposium of Electronic Art), Brisbane 2024 Dahkki Megan Beckwith (4980779)

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Correlation between subjective depth (D) and normalized EVA (degrees). Dahkki Mohammed Safayet Arefin (22683505)

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The EVA as predicted by eye movement end depth and participant (data from Fig 4b). Dahkki Mohammed Safayet Arefin (22683505)

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The experiment placed targets at 4 different depths, resulting in 12 different vergence eye movements. Measurements are expressed in meters (m) and diopters (D). Dahkki Mohammed Safayet Arefin (22683505)

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The EVA as predicted Eq 2, the linear mixed effects model. Dahkki Mohammed Safayet Arefin (22683505)

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The Eye Vergence Angle (EVA) as predicted by (a) environment and eye movement end depth in meters, and (b) as predicted by eye movement end depth in . Dahkki Mohammed Safayet Arefin (22683505)

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Predicting the vergence stability hypothesis (H3): reducing the maximal model to the fitted model. Dahkki Mohammed Safayet Arefin (22683505)

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Analysis of Eq 4: the fitted model testing whether subjective depth judgments would be underestimated, and that EVA would provide a more veridical depth estimate than subjective de... Dahkki Mohammed Safayet Arefin (22683505)

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(a) The visual stimulus was a Landolt C resolving to a fixation cross, resulting in a four-alternative forced choice visual discrimination task. Dahkki Mohammed Safayet Arefin (22683505)

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Analysis of Eq 2, the fitted model testing the effect of end depth (Hypothesis H1) and environment (Hypothesis H2) on EVA. Dahkki Mohammed Safayet Arefin (22683505)

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The geometry of the Eye Vergence Angle (EVA) while fixating on a near and far target. Dahkki Mohammed Safayet Arefin (22683505)

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Eye Vergence Angle (EVA) calculation and an example of unprocessed eye tracking data. Dahkki Mohammed Safayet Arefin (22683505)

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A zoomed-in view of participant 11 from Fig 11. Dahkki Mohammed Safayet Arefin (22683505)

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Predicting the natural log ratio of XR target depth over real target depth (Hypothesis H4): reducing the maximal model to the fitted model. Dahkki Mohammed Safayet Arefin (22683505)

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Predicting the eye vergence angle by end depth (Hypothesis H1) and environment (Hypothesis H2): reduction of the maximal model to the fitted model. Dahkki Mohammed Safayet Arefin (22683505)

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A zoomed-in view of participant 11 from Fig 8. Dahkki Mohammed Safayet Arefin (22683505)

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Analysis of Eq 3: the fitted model testing vergence stability (Hypothesis H3). Dahkki Mohammed Safayet Arefin (22683505)

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The natural log ratio of Real target depth over XR target depth, plotted as points against the eye movement end depth, environment (AR, VR), and measure (EVA, Subjective Depth). Dahkki Mohammed Safayet Arefin (22683505)

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The vergence stability hypothesis (H3), tested with Eq 3: Dahkki Mohammed Safayet Arefin (22683505)

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