MineXR: Mining Personalized Extended Reality Interfaces

Hyunsung Cho, Yukang Yan, Kashyap Todi, Mark Parent, Missie Smith, Tanya Jonker, Hrvoje Benko, David Lindlbauer.
Published at ACM CHI 2024
Teaser image

Abstract

Extended Reality (XR) interfaces offer engaging user experiences, but their effective design requires a nuanced understanding of user behavior and preferences. This knowledge is challenging to obtain without the widespread adoption of XR devices. We introduce MineXR, a design mining workflow and data analysis platform for collecting and analyzing personalized XR user interaction and experience data. MineXR enables elicitation of personalized interfaces directly from users: for any particular context, users create interface elements using application snapshots from their own smartphone, place them in the environment, and simultaneously preview the resulting XR layout on a headset. Using MineXR, we contribute a dataset of personalized XR interfaces collected from 31 participants, consisting of 695 XR widgets created from 178 unique applications. We provide insights for XR widget functionalities, categories, clusters, UI element types, and placement. Our open-source tools and data support researchers and designers in developing future XR interfaces.

More information

Source code and dataset available at https://github.com/Augmented-Perception-Lab/MineXR

Materials

Bibtex

@inproceedings {Cho24, 
 author = {Cho, Hyunsung and Yan, Yukang and Todi, Kashyap and Parent, Mark and Smith, Missie and Jonker, Tanya and Benko, Hrvoje and Lindlbauer, David}, 
 title = {MineXR: Mining Personalized Extended Reality Interfaces}, 
 year = {2024}, 
 publisher = {Association for Computing Machinery}, 
 address = {New York, NY, USA}, 
 url = {https://doi.org/10.1145/3613904.3642394}, 
 doi = {10.1145/3613904.3642394}, 
 keywords = {Extended Reality, Personalized Interfaces, Interface Mining}, 
 location = {Honolulu, HI, USA}, 
 series = {CHI '24} 
 }