AvatAR: An immersive analysis environment for human motion data combining interactive 3D avatars and trajectories

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributed

Contributors

Abstract

Analysis of human motion data can reveal valuable insights about the utilization of space and interaction of humans with their environment. To support this, we present AvatAR, an immersive analysis environment for the in-situ visualization of human motion data, that combines 3D trajectories with virtual avatars showing people's detailed movement and posture. Additionally, we describe how visualizations can be embedded directly into the environment, showing what a person looked at or what surfaces they touched, and how the avatar's body parts can be used to access and manipulate those visualizations. AvatAR combines an AR HMD with a tablet to provide both mid-air and touch interaction for system control, as well as an additional overview device to help users navigate the environment. We implemented a prototype and present several scenarios to show that AvatAR can enhance the analysis of human motion data by making data not only explorable, but experienceable.

Details

Original languageEnglish
Title of host publicationProceedings of the ACM Conference on Human Factors in Computing Systems (CHI)
EditorsSimone Barbosa, Cliff Lampe, Caroline Appert, David A. Shamma, Steven Drucker, Julie Williamson, Koji Yatani
Pages23:1-23:15
Number of pages15
ISBN (electronic)978-1-4503-9157-3
Publication statusPublished - 2 May 2022
Peer-reviewedNo

External IDs

Scopus 85130554142
Mendeley 9400561e-4605-342e-a42d-fc3fa9f3d89d
dblp conf/chi/ReipschlagerBDM22
unpaywall 10.1145/3491102.3517676
ORCID /0000-0002-2176-876X/work/151435427

Keywords

Keywords

  • Immersive Analytics, In-situ visualisation, analysing space utilization, augmented/mixed reality, human motion data, motion analysis