Context-Aware Mixed Reality: A Learning-based Framework for Semantic-level Interaction
Affiliation
Bournemouth University; University of Chester; University of BradfordPublication Date
2019-11-14
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Mixed Reality (MR) is a powerful interactive technology for new types of user experience. We present a semantic-based interactive MR framework that is beyond current geometry-based approaches, offering a step change in generating high-level context-aware interactions. Our key insight is that by building semantic understanding in MR, we can develop a system that not only greatly enhances user experience through object-specific behaviors, but also it paves the way for solving complex interaction design challenges. In this paper, our proposed framework generates semantic properties of the real-world environment through a dense scene reconstruction and deep image understanding scheme. We demonstrate our approach by developing a material-aware prototype system for context-aware physical interactions between the real and virtual objects. Quantitative and qualitative evaluation results show that the framework delivers accurate and consistent semantic information in an interactive MR environment, providing effective real-time semantic level interactions.Citation
Chen, L., Tang, W., John, N, W., Wan, T, R. & Zhang, J, J. (2019). Context-Aware Mixed Reality: A Learning-based Framework for Semantic-level Interaction. Computer Graphics Forum, 39(1), 484-496.Publisher
WileyJournal
Computer Graphics ForumAdditional Links
https://onlinelibrary.wiley.com/journal/14678659Type
ArticleDescription
This is the peer reviewed version of the following article: Chen, L., Tang, W., John, N, W., Wan, T, R. & Zhang, J, J. (2019). Context-Aware Mixed Reality: A Learning-based Framework for Semantic-level Interaction. Computer Graphics Forum, which has been published in final form at https://doi.org/10.1111/cgf.13887. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived VersionsISSN
0167-7055EISSN
1467-8659ae974a485f413a2113503eed53cd6c53
10.1111/cgf.13887
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Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc-nd/4.0/