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Crowdsourcing design guidance for contextual adaptation of text content in augmented reality
- Source :
- CHI
- Publication Year :
- 2021
- Publisher :
- Association for Computing Machinery, Inc, 2021.
-
Abstract
- Funding: This work was supported by EPSRC (grants EP/R004471/1 and EP/S027432/1). Supporting data for this publication is available at https://doi.org/10.17863/CAM.62931. Augmented Reality (AR) can deliver engaging user experiences that seamlessly meld virtual content with the physical environment. However, building such experiences is challenging due to the developer's inability to assess how uncontrolled deployment contexts may infuence the user experience. To address this issue, we demonstrate a method for rapidly conducting AR experiments and real-world data collection in the user's own physical environment using a privacy-conscious mobile web application. The approach leverages the large number of distinct user contexts accessible through crowdsourcing to efficiently source diverse context and perceptual preference data. The insights gathered through this method complement emerging design guidance and sample-limited lab-based studies. The utility of the method is illustrated by reexamining the design challenge of adapting AR text content to the user's environment. Finally, we demonstrate how gathered design insight can be operationalized to provide adaptive text content functionality in an AR headset. Publisher PDF
- Subjects :
- QA75
Computer science
QA75 Electronic computers. Computer science
Context (language use)
Mobile Web
02 engineering and technology
Augmented reality
Crowdsourcing
QA76
User experience design
QA76 Computer software
Human–computer interaction
0202 electrical engineering, electronic engineering, information engineering
0501 psychology and cognitive sciences
Adaptation (computer science)
050107 human factors
MCC
Data collection
Operationalization
business.industry
05 social sciences
020207 software engineering
DAS
NIS
Computer Graphics and Computer-Aided Design
Human-Computer Interaction
Privacy
business
Software
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- CHI
- Accession number :
- edsair.doi.dedup.....d45e524482a94d7eb7a1434f3d61221c