Towards an Understanding of Augmented Reality Extensions for Existing 3D Data Analysis Tools
Description:
We present an observational study with domain experts to understand how augmented reality (AR) extensions to traditional PC-based data analysis tools can help particle physicists to explore and understand 3D data. Our goal is to allow researchers to integrate stereoscopic AR-based visual representations and interaction techniques into their tools, and thus ultimately to increase the adoption of modern immersive analytics techniques in existing data analysis workflows. We use Microsoft's HoloLens as a lightweight and easily maintainable AR headset and replicate existing visualization and interaction capabilities on both the PC and the AR view. We treat the AR headset as a second yet stereoscopic screen, allowing researchers to study their data in a connected multi-view manner. Our results indicate that our collaborating physicists appreciate a hybrid data exploration setup with an interactive AR extension to improve their understanding of particle collision events.
Paper download: (11.4 MB)
Study materials and data:
Our study materials and data can be found in the following OSF repositories: osf.io/7qegs and osf.io/ekdvr.
Xiyao Wang, Lonni Besançon, David Rousseau, Mickael Sereno, Mehdi Ammi, and Tobias Isenberg (2020) Towards an Understanding of Augmented Reality Extensions for Existing 3D Data Analysis Tools. In Joanna McGrenere and Andy Cockburn, eds., Proceedings of the Annual Conference on Human Factors in Computing Systems (CHI, April 25–30, Honolulu, HI, USA). ACM, New York, article no. 528, 13 pages, 2020.
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BibTeX entry:
@INPROCEEDINGS{Wang:2020:TUA,
author = {Xiyao Wang and Lonni Besan{\c{c}}on and David Rousseau and Mickael Sereno and Mehdi Ammi and Tobias Isenberg},
title = {Towards an Understanding of Augmented Reality Extensions for Existing {3D} Data Analysis Tools},
booktitle = {Proceedings of the Annual Conference on Human Factors in Computing Systems (CHI, April 25--30, Honolulu, HI, USA)},
OPTeditor = {Joanna McGrenere and Andy Cockburn},
year = {2020},
pages = {528:1--528:13},
articleno = {528},
numpages = {13},
publisher = {ACM},
address = {New York},
doi = {10.1145/3313831.3376657},
doi_url = {https://doi.org/10.1145/3313831.3376657},
oa_hal_url = {https://hal.science/hal-02442690},
osf_url = {https://osf.io/7qegs/},
osf_url2 = {https://osf.io/ekdvr/},
url = {https://tobias.isenberg.cc/p/Wang2020TUA},
pdf = {https://tobias.isenberg.cc/personal/papers/Wang_2020_TUA.pdf},
}
Other References:
Xiyao Wang, Lonni Besançon, Florimond Guéniat, Mickael Sereno, Mehdi Ammi, and Tobias Isenberg (2019) A Vision of Bringing Immersive Visualization to Scientific Workflows. In Barrett Ens, Maxime Cordeil, Ulrich Engelke, Marcos Serrano, Wesley Willett, and Benjamin Bach, eds., Proceedings of the CHI Workshop on Immersive Analytics: Interaction Design and Prototyping for Immersive Analytics. 2019.
×
BibTeX entry:
@INPROCEEDINGS{Wang:2019:VBI,
author = {Xiyao Wang and Lonni Besan{\c{c}}on and Florimond Gu{\'e}niat and Mickael Sereno and Mehdi Ammi and Tobias Isenberg},
title = {A Vision of Bringing Immersive Visualization to Scientific Workflows},
booktitle = {Proceedings of the CHI Workshop on Immersive Analytics: Interaction Design and Prototyping for Immersive Analytics},
OPTeditor = {Barrett Ens and Maxime Cordeil and Ulrich Engelke and Marcos Serrano and Wesley Willett and Benjamin Bach},
year = {2019},
oa_hal_url = {https://hal.science/hal-02053969},
url = {https://tobias.isenberg.cc/p/Wang2020TUA},
url2 = {https://hal.archives-ouvertes.fr/hal-02053969},
pdf = {https://tobias.isenberg.cc/personal/papers/Wang_2019_VBI.pdf},
}
Xiyao Wang (2020) Augmented Reality Environments for the Interactive Exploration of 3D Data. PhD thesis, Université Paris-Saclay, France, December 2020.
(11.4 MB)
