Providing plasticity and redistribution for 3D user interfaces using the D3PART model

Lacoche, Jérémy; Duval, Thierry; Arnaldi, Bruno; Maisel, Éric; Royan, Jérôme

doi:10.1007/s12193-017-0239-x

Cited by 3 publications

(1 citation statement)

References 32 publications

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“…Our goal is to be able to integrate our prediction models in frameworks for the creation of adaptive 3D user interfaces. For instance, with the integration of a user model, it could be used seamlessly in the CATHI framework [15] or with the D3PART model [14] in order to compute the suitability score of interaction components.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Based Interaction Technique Selection for 3D User Interfaces

Lacoche

Duval

Arnaldi

et al. 2019

Virtual Reality and Augmented Reality

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A 3D user interface can be adapted in multiple ways according to each user's needs, skills and preferences. Such adaptation can consist in changing the user interface layout or its interaction techniques. Personalization systems which are based on user models can automatically determine the configuration of a 3D user interface in order to fit a particular user. In this paper, we propose to explore the use of machine learning in order to propose a 3D selection interaction technique adapted to a target user. To do so, we built a dataset with 51 users on a simple selection application in which we recorded each user profile, his/her results to a 2D Fitts Law based pre-test and his/her preferences and performances on this application for three different interaction techniques. Our machine learning algorithm based on Support Vector Machines (SVMs) trained on this dataset proposes the most adapted interaction technique according to the user profile or his/her result to the 2D selection pre-test. Our results suggest the interest of our approach for personalizing a 3D user interface according to the target user but it would require a larger dataset in order to increase the confidence about the proposed adaptations.

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Section: Introductionmentioning

confidence: 99%

Machine Learning Based Interaction Technique Selection for 3D User Interfaces

Lacoche

Duval

Arnaldi

et al. 2019

Virtual Reality and Augmented Reality

Self Cite

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INTERVALES: INTERactive Virtual and Augmented framework for industriaL Environment and Scenarios

Richard

Havard

His

et al. 2021

Advanced Engineering Informatics

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Virtual Versus Reality: A Systematic Review of Real-World Built Environment Tasks Performed in CAVEs and a Framework for Performance and Experience Evaluation

Pogmore,

Davies,

Cooke

2024

Virtual Worlds

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With operations in the built environment becoming increasingly data-rich (via Building Information Models and Internet of Things devices) and the rapid development of highly immersive environments, there are new opportunities for components of traditional “real-world” tasks to be undertaken in a “virtual” environment. However, an approach to compare both subjective (psychological) and objective (task-based) performance in real and virtual environments is rarely used in this context. This paper begins by introducing the industrial, technological, and psychological context of real-world and virtual tasks. A systematic review of the application of CAVE Automatic Virtual Environments (CAVEs) for “virtual” built environment tasks is conducted, and research gaps regarding the development of systems and comparison of task environments (CAVE and real-world condition) is identified. A theoretical framework to assess task performance is developed, and a novel practical experiment to compare participant(s) psychological and decision-making performance for an identical task in the real world and in a CAVE is proposed.

show abstract

Providing plasticity and redistribution for 3D user interfaces using the D3PART model

Cited by 3 publications

References 32 publications

Machine Learning Based Interaction Technique Selection for 3D User Interfaces

Machine Learning Based Interaction Technique Selection for 3D User Interfaces

INTERVALES: INTERactive Virtual and Augmented framework for industriaL Environment and Scenarios

Virtual Versus Reality: A Systematic Review of Real-World Built Environment Tasks Performed in CAVEs and a Framework for Performance and Experience Evaluation

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