Transforming Procedural Instructions into In-Situ Augmented Reality Guides with InstructAR

Following manual procedural instructions can often be frustrating due to the mental gap between the instructions and their real-world application. Variations in settings can further compound this confusion for those attempting to follow them. To address this problem, we propose InstructAR, a system under development that bridges textual instructions with the real world through Augmented Reality (AR) guides. With this tool, users can easily follow clear and actionable step-by-step instructions, as related objects are highlighted and AR guides indicate necessary actions. InstructAR also provides feedback upon task completion. This proof-of-concept leverages Natural Language Processing and Computer Vision techniques. Our work aims to reduce cognitive load and errors, making it easier for users to follow manual procedural instructions accurately.

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Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1145/3672539.3686321
Citations
2
Primary Topic
Augmented Reality Applications
Type
article
Field-Weighted Citation Impact
0.50
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article

Transforming Procedural Instructions into In-Situ Augmented Reality Guides with InstructAR

Panayu Keelawat, Ryo Suzuki
2 citations
Augmented Reality Applications
0.50
article

Transforming Procedural Instructions into In-Situ Augmented Reality Guides with InstructAR

Panayu Keelawat, Ryo Suzuki
article en
2 citations

Abstract

Following manual procedural instructions can often be frustrating due to the mental gap between the instructions and their real-world application. Variations in settings can further compound this confusion for those attempting to follow them. To address this problem, we propose InstructAR, a system under development that bridges textual instructions with the real world through Augmented Reality (AR) guides. With this tool, users can easily follow clear and actionable step-by-step instructions, as related objects are highlighted and AR guides indicate necessary actions. InstructAR also provides feedback upon task completion. This proof-of-concept leverages Natural Language Processing and Computer Vision techniques. Our work aims to reduce cognitive load and errors, making it easier for users to follow manual procedural instructions accurately.

University of Calgary (CA), Virginia Tech (US)
Openalex Percentile: Top 34%
Augmented Reality Applications
0.50
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