Abstract
AbstractThe main element of extended reality (XR) environments is behavior-rich 3D content consisting of objects that act and interact with one another as well as with users. Such actions and interactions constitute the evolution of the content over time. Multiple application domains of XR, e.g., education, training, marketing, merchandising, and design, could benefit from the analysis of 3D content changes based on general or domain knowledge comprehensible to average users or domain experts. Such analysis can be intended, in particular, to monitor, comprehend, examine, and control XR environments as well as users’ skills, experience, interests and preferences, and XR objects’ features. However, it is difficult to achieve as long as XR environments are developed with methods and tools that focus on programming and 3D modeling rather than expressing domain knowledge accompanying content users and objects, and their behavior. The main contribution of this paper is an approach to creating explorable knowledge-based XR environments with semantic annotations. The approach combines description logics with aspect-oriented programming, which enables knowledge representation in an arbitrary domain as well as transformation of available environments with minimal users’ effort. We have implemented the approach using well-established development tools and exemplify it with an explorable immersive car showroom. The approach enables efficient creation of explorable XR environments and knowledge acquisition from XR.
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Reference60 articles.
1. Autodesk (2020a) 3ds Max. https://www.autodesk.pl/products/3ds-max/overview
2. Autodesk (2020b) Motion builder. https://www.autodesk.com/products/motionbuilder/overview
3. Ben Ellefi M, Drap P, Papini O, Merad D, Royer J, Nawaf M, Nocerino E, Hyttinen K, Sourisseau J, Gambin T, et al. (2019) Ontology-based web tools for retrieving photogrammetric cultural heritage models. Underwater 3D Recording & Modeling ISPRS, Limassol
4. Berners-Lee T, Hendler J, Lassila O (2001) The semantic web. Sci Am 284 (5):34–43. http://www.sciam.com/article.cfm?articleID=00048144-10D2-1C70-84A9809EC588EF21
5. Blender Foundation (2020) Blender. http://www.blender.org
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