Feel the Globe: Enhancing the Perception of Immersive Spherical Visualizations with Tangible Proxies

Englmeier, David; Schonewald, Isabel; Butz, Andreas; Höllerer, Tobias

doi:10.1109/vr.2019.8797869

Cited by 14 publications

(5 citation statements)

References 24 publications

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“…We believe more sophisticated customized tangible devices could be more effective for certain types of tasks, such as the ones in Refs. [37][38][39] and those devices could be interesting to test in future studies. Additionally, the design space of embodiment on desktop and in VR is huge.…”

Section: Discussionmentioning

confidence: 99%

“…Various studies have confirmed the benefits of using 3D input devices as physical proxies. [32][33][34][35][36][37][38] Meanwhile, Hand 19 and Besanc xon et al 18 provided comprehensive reviews of such 3D devices. However, many tangible 3D input devices (e.g.…”

Section: Tangible Proxies For 3d Interactionmentioning

confidence: 99%

“…those ones in Refs. [37][38][39] ) are customized for studies and not easily accessible to ordinary users. Thus, in our study, we chose to test a broadly available trackball mouse as our proxy.…”

Section: Tangible Proxies For 3d Interactionmentioning

confidence: 99%

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Is embodied interaction beneficial? A study on navigating network visualizations

Huang

Pfister

Yang

2023

Information Visualization

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Network visualizations are commonly used to analyze relationships in various contexts, such as social, biological, and geographical interactions. To efficiently explore a network visualization, the user needs to quickly navigate to different parts of the network and analyze local details. Recent advancements in display and interaction technologies inspire new visions for improved visualization and interaction design. Past research into network design has identified some key benefits to visualizing networks in 3D versus 2D. However, little work has been done to study the impact of varying levels of embodied interaction on network analysis. We present a controlled user study that compared four network visualization environments featuring conditions and hardware that leveraged different amounts of embodiment and visual perception ranging from a 2D visualization desktop environment with a standard mouse to a 3D visualization virtual reality environment. We measured the accuracy, speed, perceived workload, and preferences of 20 participants as they completed three network analytic tasks, each of which required unique navigation and substantial effort to complete. For the task that required participants to iterate over the entire visualization rather than focus on a specific area, we found that participants were more accurate using a VR HMD and a trackball mouse than conventional desktop settings. From a workload perspective, VR was generally considered the least mentally demanding and least frustrating to use in two of our three tasks. It was also preferred and ranked as the most effective and visually appealing condition overall. However, using VR to compare two side-by-side networks was difficult, and it was similar to or slower than other conditions in two of the three tasks. Overall, the accuracy and workload advantages of conditions with greater embodiment in specific tasks suggest promising opportunities to create more effective environments in which to analyze network visualizations.

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Section: Discussionmentioning

confidence: 99%

Section: Tangible Proxies For 3d Interactionmentioning

confidence: 99%

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Is embodied interaction beneficial? A study on navigating network visualizations

Huang

Pfister

Yang

2023

Information Visualization

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“…However, when compared to an interaction technique using two mid-air input devices, the tangible box yielded higher precision and lower task accomplishment time. Using a VR HMD, Englmeier et al tested a passive tangible sphere also made of transparent acrylic [11]. They experimented with spheres of diameter 25 cm and 40 cm weighting around 1 kg and 2.4 kg, respectively.…”

Section: Passive Tangible Volumes In Vr and Armentioning

confidence: 99%

“…We thus focus on HPCDs interactions that satisfy the requirement of the two hands remaining in contact with the display. As a result, most menu and widget interaction techniques that have been designed in the context of VR and AR cannot be directly transferred to this type of HPCDs, although recent work in VR has investigated similar two-handed tangible interaction [11,48]. In addition, we focus on a spherical shape for the display because of its seamless surface and its support for the independent and continuous control of the three rotations (yaw/pitch/roll).…”

Section: Introductionmentioning

confidence: 99%

GyroSuite

Thibault

Troccaz

Rochet-Capellan

et al. 2020

Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology

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Handheld Perspective-Corrected Displays (HPCDs) are physical objects that have a notable volume and that display a virtual 3D scene on their entire surface. Being handheld, they create the illusion of holding the scene in a physical container (the display). This has strong benefits for the intuitiveness of 3D interaction: manipulating objects of the virtual scene amounts to physical manipulations of the display. HPCDs have been limited so far to technical demonstrators and experimental tools to assess their merits. However, they show great potential as interactive systems for actual 3D applications. This requires that novel interactions be created to go beyond object manipulation and to offer general-purpose services such as menu command selection and continuous parameter control.Working with a two-handed spherical HPCD, we report on the design and informal evaluations of various interaction techniques for distant object selection, scene scaling, menu interaction and continuous parameter control. In particular, our design leverages the efficient two-handed control of the rotations of the display. We demonstrate how some of these techniques can be assemble in a self-contained anatomy learning application. Novice participants used the application in a qualitative user experiment. Most participants used the application effortlessly without any training or explanations.

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