Knowledge-based approach to adaptive XR interface design for non-programmers

Author:

Maik MikołajORCID,Flotyński JakubORCID,Walczak KrzysztofORCID

Abstract

AbstractCustomizing extended reality (XR) interfaces presents a significant challenge, especially for users with limited programming expertise. This paper introduces the method for adaptation of XR interfaces (MAXI-XR), a novel approach to simplify the customization process of XR user interfaces through knowledge technologies. MAXI-XR offers a user-friendly solution for interface design, supporting users with varying levels of technical skills. The basis of MAXI-XR is its Semantic Knowledge Base, which facilitates intelligent adaptations through advanced querying and reasoning, enabling the extraction of user-specific information for context-based XR interface adaptation. The functionality of MAXI-XR is demonstrated by its application in a VR stock market data visualization system. This system demonstrates MAXI-XR’s ability to adapt to complex and data-intensive environments according to user requirements, improving the interaction experience. Furthermore, the method’s scalability and ease of maintenance make it a versatile tool for a wide range of applications beyond stock market visualization, suggesting its potential for broader adoption in various XR domains.

Funder

Narodowe Centrum Badań i Rozwoju

Publisher

Springer Science and Business Media LLC

Reference26 articles.

1. Buche, C., Bossard, C., Querrec, R., Chevaillier, P.: Pegase: a generic and adaptable intelligent system for virtual reality learning environments. Int. J. Virtual Real. 9(2), 73–85 (2010)

2. Calvary, G., Coutaz, J., Thevenin, D., Limbourg, Q., Bouillon, L., Vanderdonckt, J.: A unifying reference framework for multi-target user interfaces. Interact. Comput. 15(3), 289–308 (2003)

3. De Troyer, O., Kleinermann, F., Pellens, B., Bille, W.: Conceptual modeling for virtual reality. In John Grundy, Sven Hartmann, Alberto H. F. Laender, Leszek Maciaszek, and John F. Roddick, editors, Tutorials, posters, panels and industrial contributions at the 26th Int. Conference on Conceptual Modeling - ER 2007, volume 83 of CRPIT, pages 3–18, Auckland, New Zealand, (2007). ACS

4. Evangelista Belo, J.M., Lystbæk, M.N., Feit, A.M., Pfeuffer, K., Kán, P., Oulasvirta, A., Grønbæk, K.: Auit–the adaptive user interfaces toolkit for designing xr applications. In Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology, pages 1–16, 2022

5. Flotynski, J., Sobocinski, P., Sliwicki, M., Maik, M.: Future and backward exploration of xr environments

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3