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

Abstract

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