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AvatAR: An Immersive Analysis Environment for Human Motion Data Combining Interactive 3D Avatars and Trajectories
Patrick Reipschläger, Frederik Brudy, Raimund Dachselt, Justin Matejka, George Fitzmaurice, Fraser Anderson

CHI'22: ACM Conference on Human Factors in Computing Systems
Session: Immersion and Interaction in Visualization

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, 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.

WEB:: https://chi2022.acm.org/

Pre-recorded presentations of CHI 2022