View in EDS

3D timelines in VR: Adaptive speed for 3D data navigation on a concave timeline.

Saved in:
Bibliographic Details
Title: 3D timelines in VR: Adaptive speed for 3D data navigation on a concave timeline.
Authors: Perelman, Gary1 (AUTHOR) gary.perelman@irit.fr, Serrano, Marcos1 (AUTHOR), Marchal, Aurélien1 (AUTHOR), Dubois, Emmanuel1 (AUTHOR)
Source: International Journal of Human-Computer Studies. Jan2026, Vol. 207, pN.PAG-N.PAG. 1p.
Subjects: Data visualization, Virtual reality, Pattern perception, Three-dimensional imaging, Big data, Human behavior
Abstract: • Using a concave visualization for 3D timeline in VR allows for faster navigation than a convex or a snapshot timeline. • Using adaptive speed for the navigation in a 3D timeline in VR is faster than using a slider or a dual-speed technique. • Separating the DoFs for the zooming and panning tasks of the adaptive speed technique is preferred over the use of the same modality for both. • Using the joystick for zooming and mid-air for panning is the most efficient and preferred interaction technique for navigation in a 3D timeline in VR. • Using adaptive speed for the navigation in a 3D timeline in VR is still robust with large size datasets (10 000 items). Using position control for panning is the most efficient solution in such situations. Timelines involving 3D objects can be rendered in VR to facilitate their visualization and various forms of data analysis, such as object location or pattern detection. While different timeline shapes have been proposed in 3D, such as convex or linear, the input interaction is usually based on inherited UIs (e.g. sliders), leaving the rich VR controllers unexploited. Hence, there is still room for more efficient interaction with 3D timelines in VR. Our first contribution is the experimental comparison of a concave timeline shape against other existing shapes. We demonstrate that users prefer the concave shape, which allows for faster object selection and pattern detection. Our second contribution is the design of four controller-based navigation techniques using adaptive speed, i.e. allowing the users to instantly adjust the panning speed in the timeline. We experimentally compared their performance to two baselines: a slider widget and a dual-speed navigation technique. We demonstrate that users prefer the techniques based on adaptive speed, which allow for faster object selection and pattern detection. Finally, in a third experiment we assess the scalability of the best techniques with a timeline containing a large number of elements. Our results show that the adaptive speed technique remains the most efficient with timelines containing thousands of elements. CCS CONCEPTS • Human-centered computing ∼ Human computer interaction (HCI) ∼ Interaction techniques [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Human-Computer Studies is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Description
Abstract:• Using a concave visualization for 3D timeline in VR allows for faster navigation than a convex or a snapshot timeline. • Using adaptive speed for the navigation in a 3D timeline in VR is faster than using a slider or a dual-speed technique. • Separating the DoFs for the zooming and panning tasks of the adaptive speed technique is preferred over the use of the same modality for both. • Using the joystick for zooming and mid-air for panning is the most efficient and preferred interaction technique for navigation in a 3D timeline in VR. • Using adaptive speed for the navigation in a 3D timeline in VR is still robust with large size datasets (10 000 items). Using position control for panning is the most efficient solution in such situations. Timelines involving 3D objects can be rendered in VR to facilitate their visualization and various forms of data analysis, such as object location or pattern detection. While different timeline shapes have been proposed in 3D, such as convex or linear, the input interaction is usually based on inherited UIs (e.g. sliders), leaving the rich VR controllers unexploited. Hence, there is still room for more efficient interaction with 3D timelines in VR. Our first contribution is the experimental comparison of a concave timeline shape against other existing shapes. We demonstrate that users prefer the concave shape, which allows for faster object selection and pattern detection. Our second contribution is the design of four controller-based navigation techniques using adaptive speed, i.e. allowing the users to instantly adjust the panning speed in the timeline. We experimentally compared their performance to two baselines: a slider widget and a dual-speed navigation technique. We demonstrate that users prefer the techniques based on adaptive speed, which allow for faster object selection and pattern detection. Finally, in a third experiment we assess the scalability of the best techniques with a timeline containing a large number of elements. Our results show that the adaptive speed technique remains the most efficient with timelines containing thousands of elements. CCS CONCEPTS • Human-centered computing ∼ Human computer interaction (HCI) ∼ Interaction techniques [ABSTRACT FROM AUTHOR]
ISSN:10715819
DOI:10.1016/j.ijhcs.2025.103672