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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
January 2022 · Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI)

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.

DOI PDF

Figures

Figure 1: An overview of some of the aspects of AvatAR: (a) The virtual avatars of two persons, one with an active 3D trajectory for the left hand, and the tablet with the foor plan visible, which sho
Figure 2: The core components of AvatAR: The virtual hu-manoid avatar visualizing a person’s detailed posture, a 3D trajectory providing an overview of movement, and the ac-companying handheld tablet
Figure 3: Overview of AvatAR’s various visualization tecl niques and the body parts of the virtual avatar from whic they can be accessed.
Figure 4: (a) One virtual 3D avatar interacting with the environment with another one walking in the background. (b) Marking menu for the avatar’s hand with the item for trajectories being selected. (
Figure 5: (a) Ghost Preview technique with two pinned hand ghosts touching the display. (b) Specter Visualizations technique of just the avatar’s hands, showing past and future time frames as semi-tra
Figure 6: (a) Visualization of interactions with the environment, here showing touches on an interactive display with the center one being highlighted. (b) Visualization of where the feet of two avata
Figure 7: (a) The hands of avatars connecting as people shake hands to greet each other. (b) A person performing a dance choreography with their hand movements visible as a trajectory and the position

BibTeX

@inproceedings{10.1145/3491102.3517676,
 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.},
 address = {New York, NY, USA},
 articleno = {23},
 author = {Reipschläger, Patrick and Brudy, Frederik and Dachselt, Raimund and Matejka, Justin and Fitzmaurice, George and Anderson, Fraser},
 booktitle = {Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems},
 doi = {10.1145/3491102.3517676},
 isbn = {9781450391573},
 keywords = {human motion data, motion analysis, Immersive Analytics, In-situ visualisation, augmented/mixed reality, analysing space utilization},
 location = {New Orleans, LA, USA},
 numpages = {15},
 publisher = {Association for Computing Machinery},
 series = {CHI '22},
 title = {AvatAR: An Immersive Analysis Environment for Human Motion Data Combining Interactive 3D Avatars and Trajectories},
 url = {https://doi.org/10.1145/3491102.3517676},
 year = {2022}
}