Context-Aware Mixed Reality: A Learning-Based Framework for Semantic-Level Interaction

Authors: Chen, L., Tang, W., John, N.W., Wan, T.R. and Zhang, J.J.

Journal: Computer Graphics Forum

Volume: 39

Issue: 1

Pages: 484-496

eISSN: 1467-8659

ISSN: 0167-7055

DOI: 10.1111/cgf.13887

Abstract:

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 behaviours, 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.

https://eprints.bournemouth.ac.uk/32880/

Source: Scopus

Context-Aware Mixed Reality: A Learning-Based Framework for Semantic-Level Interaction

Authors: Chen, L., Tang, W., John, N.W., Wan, T.R. and Zhang, J.J.

Journal: COMPUTER GRAPHICS FORUM

Volume: 39

Issue: 1

Pages: 484-496

eISSN: 1467-8659

ISSN: 0167-7055

DOI: 10.1111/cgf.13887

https://eprints.bournemouth.ac.uk/32880/

Source: Web of Science (Lite)

Context-Aware Mixed Reality: A Learning-based Framework for Semantic-level Interaction

Authors: Chen, L., Tang, W., John, N.W., Wan, T.R. and Zhang, J.J.

Journal: Computer Graphics Forum

Publisher: Wiley-Blackwell

Abstract:

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 critical 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.

https://eprints.bournemouth.ac.uk/32880/

https://onlinelibrary.wiley.com/journal/14678659

Source: Manual

Context-Aware Mixed Reality: A Learning-based Framework for Semantic-level Interaction.

Authors: Chen, L., Tang, W., John, N.W., Wan, T.R. and Zhang, J.J.

Journal: Computer Graphics Forum

Volume: 39

Issue: 1

Pages: 484-496

ISSN: 0167-7055

Abstract:

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 critical 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.

https://eprints.bournemouth.ac.uk/32880/

Source: BURO EPrints