Abstract
We present an optimization-based approach for Mixed Reality (MR) systems to automatically control when and where applications are shown, and how much information they display. Currently, content creators design applications, and users then manually adjust which applications are visible and how much information they show. This choice has to be adjusted every time users switch context, i.e., whenever they switch their task or environment. Since context switches happen many times a day, we believe that MR interfaces require automation to alleviate this problem. We propose a real-time approach to automate this process based on users' current cognitive load and knowledge about their task and environment. Our system adapts which applications are displayed, how much information they show, and where they are placed. We formulate this problem as a mix of rule-based decision making and combinatorial optimization which can be solved efficiently in real-time. We present a set of proof-of-concept applications showing that our approach is applicable in a wide range of scenarios. Finally, we show in a dual-task evaluation that our approach decreased secondary tasks interactions by 36%.
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BibTeX (Download)
@inproceedings{lindlbauer19,
title = {Context-Aware Online Adaptation of Mixed Reality Interfaces},
author = {David Lindlbauer and Anna Maria Feit and Otmar Hilliges},
url = {https://ait.ethz.ch/projects/2019/computationalMR/},
doi = {10.1145/3332165.3347945},
isbn = {9781450368162},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
booktitle = {Symposium on User Interface Software and Technology},
publisher = {ACM},
series = {UIST '19},
abstract = {We present an optimization-based approach for Mixed Reality (MR) systems to automatically control when and where applications are shown, and how much information they display. Currently, content creators design applications, and users then manually adjust which applications are visible and how much information they show. This choice has to be adjusted every time users switch context, i.e., whenever they switch their task or environment. Since context switches happen many times a day, we believe that MR interfaces require automation to alleviate this problem. We propose a real-time approach to automate this process based on users' current cognitive load and knowledge about their task and environment. Our system adapts which applications are displayed, how much information they show, and where they are placed. We formulate this problem as a mix of rule-based decision making and combinatorial optimization which can be solved efficiently in real-time. We present a set of proof-of-concept applications showing that our approach is applicable in a wide range of scenarios. Finally, we show in a dual-task evaluation that our approach decreased secondary tasks interactions by 36%.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}