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License: Custom Terms Author Name: Bulling, Andreas

1 to 5 of 5 Results

VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data) Apr 8, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations" Wang, Yao; Bulling, Andreas, 2024, "VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)", https://doi.org/10.18419/darus-3138, DaRUS, V1, UNF:6:NwphGtoYrBQqd2TyRh0OHA== [fileUNF] This dataset contains stimuli and collected participant data of VisRecall++. The structure of the dataset is described in the README-File. Further, if you are interested in related codes of the publication, you can find a copy of the code repository (see Metadata for Research Sof...
Saliency3D: A 3D Saliency Dataset Collected on Screen (Dataset and Experiment Application) Mar 22, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations" Wang, Yao; Bulling, Andreas, 2024, "Saliency3D: A 3D Saliency Dataset Collected on Screen (Dataset and Experiment Application)", https://doi.org/10.18419/darus-4101, DaRUS, V1 While visual saliency has recently been studied in 3D, the experimental setup for collecting 3D saliency data can be expensive and cumbersome. To address this challenge, we propose a novel experimental design that utilizes an eye tracker on a screen to collect 3D saliency data. O...
Data for "Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography" Oct 20, 2022 - Perceptual User Interfaces Bulling, Andreas, 2022, "Data for "Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography"", https://doi.org/10.18419/darus-3134, DaRUS, V1 This dataset was recorded to investigate the problem of recognising reading activity from eye movements. The experimental setup was designed with two main objectives in mind: (1) to record eye movements in an unobtrusive manner in a mobile real-world setting, and (2) to evaluate...
Data for "Eye Movement Analysis for Activity Recognition Using Electrooculography" Oct 17, 2022 - Perceptual User Interfaces Bulling, Andreas, 2022, "Data for "Eye Movement Analysis for Activity Recognition Using Electrooculography"", https://doi.org/10.18419/darus-3135, DaRUS, V1 This dataset was recorded to investigate the problem of recognising common office activities from eye movements. The experimental scenario involved five office-based activities - copying a text, reading a printed paper, taking handwritten notes, watching a video, and browsing the...
Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering" Jun 21, 2022 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations" Wang, Yao; Bulling, Andreas, 2022, "Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"", https://doi.org/10.18419/darus-2826, DaRUS, V1, UNF:6:AuvgRc09o1rESd63AqlW9Q== [fileUNF] Despite its importance for assessing the effectiveness of communicating information visually, fine-grained recallability of information visualisations has not been studied quantitatively so far. We propose a question-answering paradigm to study visualisation recallability and pre...

VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)

Apr 8, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"

Wang, Yao; Bulling, Andreas, 2024, "VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)", https://doi.org/10.18419/darus-3138, DaRUS, V1, UNF:6:NwphGtoYrBQqd2TyRh0OHA== [fileUNF]

This dataset contains stimuli and collected participant data of VisRecall++. The structure of the dataset is described in the README-File. Further, if you are interested in related codes of the publication, you can find a copy of the code repository (see Metadata for Research Sof...

Saliency3D: A 3D Saliency Dataset Collected on Screen (Dataset and Experiment Application)

Mar 22, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"

Wang, Yao; Bulling, Andreas, 2024, "Saliency3D: A 3D Saliency Dataset Collected on Screen (Dataset and Experiment Application)", https://doi.org/10.18419/darus-4101, DaRUS, V1

While visual saliency has recently been studied in 3D, the experimental setup for collecting 3D saliency data can be expensive and cumbersome. To address this challenge, we propose a novel experimental design that utilizes an eye tracker on a screen to collect 3D saliency data. O...

Data for "Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography"

Oct 20, 2022 - Perceptual User Interfaces

Bulling, Andreas, 2022, "Data for "Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography"", https://doi.org/10.18419/darus-3134, DaRUS, V1

This dataset was recorded to investigate the problem of recognising reading activity from eye movements. The experimental setup was designed with two main objectives in mind: (1) to record eye movements in an unobtrusive manner in a mobile real-world setting, and (2) to evaluate...

Data for "Eye Movement Analysis for Activity Recognition Using Electrooculography"

Oct 17, 2022 - Perceptual User Interfaces

Bulling, Andreas, 2022, "Data for "Eye Movement Analysis for Activity Recognition Using Electrooculography"", https://doi.org/10.18419/darus-3135, DaRUS, V1

This dataset was recorded to investigate the problem of recognising common office activities from eye movements. The experimental scenario involved five office-based activities - copying a text, reading a printed paper, taking handwritten notes, watching a video, and browsing the...

Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"

Jun 21, 2022 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"

Wang, Yao; Bulling, Andreas, 2022, "Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"", https://doi.org/10.18419/darus-2826, DaRUS, V1, UNF:6:AuvgRc09o1rESd63AqlW9Q== [fileUNF]

Despite its importance for assessing the effectiveness of communicating information visually, fine-grained recallability of information visualisations has not been studied quantitatively so far. We propose a question-answering paradigm to study visualisation recallability and pre...

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