Context-Aware Mixed Reality: A Learning-based Framework for Semantic-level Interaction
- Submitting institution
-
University of Chester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 10034/622767
- Type
- D - Journal article
- DOI
-
10.1111/cgf.13887
- Title of journal
- Computer Graphics Forum
- Article number
- -
- First page
- 484
- Volume
- 39
- Issue
- 1
- ISSN
- 0167-7055
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- In this collaboration with Bournemouth University, we have shown how a deep semantic scene understanding methodology, combined with dense 3D scene reconstruction, can build a high‐level context‐aware and highly interactive mixed reality environment. The results of this recently published work show that the study of semantic constructions in mixed reality is worth pursuing, particularly as we can expect more complex rich mixed reality applications to be developed in the near future. We hope that this initiative to apply artificial intelligence to mixed reality offers new insight and bridges the gap between virtual and real worlds in context‐aware interactions.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -