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

@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}
}