CREATTIVE3D multimodal dataset of user behavior in virtual reality

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Auteurs principaux: Hui-Yin Wu, Florent Robert, Lucile Sassatelli, Marco Winckler, Auriane Gros, Stephen Ramanoël
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Publié: Zenodo 2024
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author Hui-Yin Wu
Florent Robert
Lucile Sassatelli
Marco Winckler
Auriane Gros
Stephen Ramanoël
author_facet Hui-Yin Wu
Florent Robert
Lucile Sassatelli
Marco Winckler
Auriane Gros
Stephen Ramanoël
contents <p>In the context of the <a href="https://project.inria.fr/creattive3d/">ANR CREATTIVE3D</a> project, we join the expertise of computer science, neuroscience, and clinical practitioners, with the aim to analyze the impact that a simulated low-vision condition has on user navigation behavior in complex road crossing scenes: a common daily situation where the difficulty to access and process visual information (e.g., traffic lights, approaching cars) in a timely fashion can lead to serious consequences on a person's safety and well-being. As a secondary objective, we also aim to investigate the potential role virtual reality could play in rehabilitation and training protocols for low-vision patients.</p> <p>This dataset contains the data as part of the study described in <a href="https://hal.science/hal-04102737">An Integrated Framework for Understanding Multimodal Embodied Experiences in Interactive Virtual Reality</a>.</p> <p>The dataset is metadata for the pre-print <a href="https://inria.hal.science/hal-04429351">Exploring, walking, and interacting in virtual reality with simulated low vision: a living contextual dataset</a></p> <p>To use this dataset, please cite:</p> <blockquote> <pre>@article{wu2025exploring, title={Exploring, walking, and interacting in virtual reality with simulated low vision: a living contextual dataset}, author={Wu, Hui-Yin and Robert, Florent and Gallo, Franz Franco and Pirkovets, Kateryna and Qu{\'e}r{\'e}, Cl{\'e}ment and Delachambre, Johanna and Ramano{\"e}l, Stephen and Gros, Auriane and Winckler, Marco and Sassatelli, Lucile and others}, journal={Scientific Data}, volume={12}, number={1}, pages={330}, year={2025}, publisher={Nature Publishing Group UK London} }<br><br>@inproceedings{robert2023integrated, title={An integrated framework for understanding multimodal embodied experiences in interactive virtual reality}, author={Robert, Florent and Wu, Hui-Yin and Sassatelli, Lucile and Ramanoel, Stephen and <br> Gros, Auriane and Winckler, Marco}, booktitle={Proceedings of the 2023 ACM International Conference on Interactive Media Experiences}, pages={14--26}, year={2023} }</pre> </blockquote> <h3> </h3> <h3>Versions</h3> <p>2024-12-18: Updated readme with description of labels, columns, and suggestions on how to start exploring the dataset. We also provide the questionnaire responses and observation notes in English (questionnaire_translation_EN.csv).</p>
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publishDate 2024
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spellingShingle CREATTIVE3D multimodal dataset of user behavior in virtual reality
Hui-Yin Wu
Florent Robert
Lucile Sassatelli
Marco Winckler
Auriane Gros
Stephen Ramanoël
virtual reality
low vision
gaze tracking
physiology
motion capture
road crossing
<p>In the context of the <a href="https://project.inria.fr/creattive3d/">ANR CREATTIVE3D</a> project, we join the expertise of computer science, neuroscience, and clinical practitioners, with the aim to analyze the impact that a simulated low-vision condition has on user navigation behavior in complex road crossing scenes: a common daily situation where the difficulty to access and process visual information (e.g., traffic lights, approaching cars) in a timely fashion can lead to serious consequences on a person's safety and well-being. As a secondary objective, we also aim to investigate the potential role virtual reality could play in rehabilitation and training protocols for low-vision patients.</p> <p>This dataset contains the data as part of the study described in <a href="https://hal.science/hal-04102737">An Integrated Framework for Understanding Multimodal Embodied Experiences in Interactive Virtual Reality</a>.</p> <p>The dataset is metadata for the pre-print <a href="https://inria.hal.science/hal-04429351">Exploring, walking, and interacting in virtual reality with simulated low vision: a living contextual dataset</a></p> <p>To use this dataset, please cite:</p> <blockquote> <pre>@article{wu2025exploring, title={Exploring, walking, and interacting in virtual reality with simulated low vision: a living contextual dataset}, author={Wu, Hui-Yin and Robert, Florent and Gallo, Franz Franco and Pirkovets, Kateryna and Qu{\'e}r{\'e}, Cl{\'e}ment and Delachambre, Johanna and Ramano{\"e}l, Stephen and Gros, Auriane and Winckler, Marco and Sassatelli, Lucile and others}, journal={Scientific Data}, volume={12}, number={1}, pages={330}, year={2025}, publisher={Nature Publishing Group UK London} }<br><br>@inproceedings{robert2023integrated, title={An integrated framework for understanding multimodal embodied experiences in interactive virtual reality}, author={Robert, Florent and Wu, Hui-Yin and Sassatelli, Lucile and Ramanoel, Stephen and <br> Gros, Auriane and Winckler, Marco}, booktitle={Proceedings of the 2023 ACM International Conference on Interactive Media Experiences}, pages={14--26}, year={2023} }</pre> </blockquote> <h3> </h3> <h3>Versions</h3> <p>2024-12-18: Updated readme with description of labels, columns, and suggestions on how to start exploring the dataset. We also provide the questionnaire responses and observation notes in English (questionnaire_translation_EN.csv).</p>
title CREATTIVE3D multimodal dataset of user behavior in virtual reality
topic virtual reality
low vision
gaze tracking
physiology
motion capture
road crossing
url https://doi.org/10.5281/zenodo.14514163