Towards Gestural Interaction with 3D Industrial Measurement Data Using HMD AR
Lecture Notes in Networks and Systems, ISSN: 2367-3389, Vol: 710 LNNS, Page: 213-221
2023
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Conference Paper Description
Despite the spread of augmented reality (AR) systems and its applications onto a number of various areas, the adoption of AR in industrial context is relatively limited. We decided to conduct an exploratory user study to define the eventual singularities that might be associated with the barriers for HMD AR technology adoption in the industrial settings, as recent works presented potential benefits of its applications with regard to specific 3D measurement data interpretation. The task-based study was designed to engage users with interaction of volumetric data of static and time series nature. We compared actions of users performed in lab vs. in situ conditions simulating real, process tomography measurement data visualisations for granular bulk solids flow in large containers. Study results revealed concrete directions for further work that might eventually enable wider adoption of HMD AR systems in the industrial context in terms of specific gestural interaction and visualisation techniques development.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85172000151&origin=inward; http://dx.doi.org/10.1007/978-3-031-37649-8_21; https://link.springer.com/10.1007/978-3-031-37649-8_21; https://dx.doi.org/10.1007/978-3-031-37649-8_21; https://link.springer.com/chapter/10.1007/978-3-031-37649-8_21
Springer Science and Business Media LLC
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