AUIT – the Adaptive User Interfaces Toolkit for Designing XR Applications

Belo, João Marcelo Evangelista; Lystbæk, Mathias N.; Feit, Anna Maria; Pfeuffer, Ken; Kán, Peter; Oulasvirta, Antti; Grønbæk, Kaj

doi:10.1145/3526113.3545651

Cited by 23 publications

(25 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We took inspiration from XR authoring tools [62], adaptive interfaces [5,7], cross-device interaction (cf. Brudy et al [6]), and prototyping toolkits [32,63].…”

Section: Design Principlesmentioning

confidence: 99%

MineXR: Mining Personalized Extended Reality Interfaces

Cho,

Yan,

Todi

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

View full text Add to dashboard Cite

Extended Reality (XR) interfaces offer engaging user experiences, but their effective design requires a nuanced understanding of user behavior and preferences. This knowledge is challenging to obtain without the widespread adoption of XR devices. We introduce MineXR, a design mining workflow and data analysis platform for collecting and analyzing personalized XR user interaction and Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

show abstract

“…We took inspiration from XR authoring tools [62], adaptive interfaces [5,7], cross-device interaction (cf. Brudy et al [6]), and prototyping toolkits [32,63].…”

Section: Design Principlesmentioning

confidence: 99%

MineXR: Mining Personalized Extended Reality Interfaces

Cho,

Yan,

Todi

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

View full text Add to dashboard Cite

show abstract

“…Commonly, these optimization-based adaptation approaches treat layout adaptation as a single-objective optimization problem, combining multiple objectives for multiple elements into a single cost to be minimized or a single utility score to be maximized and returning a single solution. Most frequently, this global criterion takes the form of a static weighted sum (e.g., [3,11,16,20,27,32,41]), which can be optimized using commercial solvers for linear programs (e.g., [11,27]) or using approximate techniques like simulated annealing (e.g., [3]). In contrast to these previous efforts, our approach treats layout adaptation as an online multi-objective optimization problem that returns a set of optimal adaptations.…”

Section: Global Criterion Optimization For Adaptive Mixed Realitymentioning

confidence: 99%

“…Our approach to real-time adaptation of MR interfaces uses multiobjective optimization to generate a varied set of optimal adaptations that users can choose from, positioning it between fully automated and fully manual adaptation. It can be invoked by a variety of triggers such as a threshold function or a regular interval [3]. Our approach can be divided into three major steps: Multi-Objective Optimization, Solution Set Reduction, and Preference Elicitation (see Figure 1c).…”

Section: Approachmentioning

confidence: 99%

“…Because MR user interfaces (UIs) coexist in the physical world, they must adapt to dynamic contextual information such as user position, pose, task, and environment [27]. This includes adapting UI layouts to meet potentially conflicting objectives, such as visibility, input availability, and relevance [3]. An MR application supporting furniture assembly, for example, should consider the user's surroundings and physical comfort when positioning interactive instructions (see Figure 1a).…”

Section: Introductionmentioning

confidence: 99%

“…To address this challenge, adaptation methods have been proposed that formalize UI placement as an optimization problem. Commonly, these formulations rely on a global criterion -an overall utility or cost score to be maximized or minimized -expressed as a weighted sum (e.g., [3,11,16,27]). Global criteria suffer from various limitations regarding the solutions they can produce and the challenges they pose for designers and end-users [29].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Pareto Optimal Layouts for Adaptive Mixed Reality

Johns

Belo

Klokmose

et al. 2023

Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

Self Cite

View full text Add to dashboard Cite

Adaptive mixed reality applications adjust their user interfaces based on the context in which they are used to provide a smooth experience for different users and environments. This involves carefully positioning UI elements, which can be challenging due to the many possible placements and need to balance competing goals. Current approaches employ global criterion optimization methods like weighted sums, which can be difficult to use, inflexible, and might not find preferred solutions. This can prevent the adaptations from meeting end-user expectations. We suggest using online multi-objective optimization methods which generate a set of Pareto optimal adaptation proposals, giving users more control and adding flexibility to the computational decision-making. We explore the feasibility of our approach by generating adaptations for a basic synthetic example and discuss relevant dimensions for a

show abstract

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

Maik,

Flotyński,

Walczak

2024

Vis Comput

View full text Add to dashboard Cite

Customizing 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.

show abstract

AUIT – the Adaptive User Interfaces Toolkit for Designing XR Applications

Cited by 23 publications

References 43 publications

MineXR: Mining Personalized Extended Reality Interfaces

MineXR: Mining Personalized Extended Reality Interfaces

Pareto Optimal Layouts for Adaptive Mixed Reality

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

Contact Info

Product

Resources

About