AvatAR: An Immersive Analysis Environment for Human Motion Data Combining Interactive 3D Avatars and Trajectories


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, virtual avatars of people’s movement, and a detailed representation of their posture. Additionally, we describe how to embed visualizations 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 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.

Patrick Reipschläger
Autodesk Research, Toronto, Ontario, Canada
Frederik Brudy
Autodesk Research, Toronto, Ontario, Canada
Raimund Dachselt
Technische Universität Dresden, Dresden, Germany
Justin Matejka
Autodesk Research, Toronto, Ontario, Canada
George Fitzmaurice
Autodesk Research, Toronto, Ontario, Canada
Fraser Anderson
Autodesk Research, Toronto, Ontario, Canada



会議: CHI 2022

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)

セッション: Immersion and Interaction in Visualization

4 件の発表
2022-05-03 01:15:00
2022-05-03 02:30:00