liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Towards an Understanding of Augmented Reality Extensions for Existing 3D Data Analysis Tools
Univ Paris Saclay, France.
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
Université Paris-Saclay, CNRS, IJCLab, Orsay, France.
Univ Paris Saclay, France.
Show others and affiliations
2020 (English)In: PROCEEDINGS OF THE 2020 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI20), ASSOC COMPUTING MACHINERY , 2020Conference paper, Published paper (Refereed)
Abstract [en]

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 Microsofts 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.

Place, publisher, year, edition, pages
ASSOC COMPUTING MACHINERY , 2020.
Keywords [en]
Immersive analytics; 3D visualization; User interface; Hybrid visualization system
National Category
Media Engineering
Identifiers
URN: urn:nbn:se:liu:diva-180248DOI: 10.1145/3313831.3376657ISI: 000696109100126PubMedID: 32836800ISBN: 978-1-4503-6708-0 (print)OAI: oai:DiVA.org:liu-180248DiVA, id: diva2:1602799
Conference
CHI Conference on Human Factors in Computing Systems (CHI), ELECTR NETWORK, apr 25-30, 2020
Available from: 2021-10-13 Created: 2021-10-13 Last updated: 2021-10-13

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Besancon, Lonni
By organisation
Media and Information TechnologyFaculty of Science & Engineering
Media Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
isbn
urn-nbn

Altmetric score

doi
pubmed
isbn
urn-nbn
Total: 12 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf