8,258 research outputs found
Grand Challenges in Immersive Analytics
The definitive version will be published in CHI 2021, May 8â13, 2021, Yokohama, JapanInternational audienceImmersive Analytics is a quickly evolving field that unites several areas such as visualisation, immersive environments, and humancomputer interaction to support human data analysis with emerging technologies. This research has thrived over the past years with multiple workshops, seminars, and a growing body of publications, spanning several conferences. Given the rapid advancement of interaction technologies and novel application domains, this paper aims toward a broader research agenda to enable widespread adoption. We present 17 key research challenges developed over multiple sessions by a diverse group of 24 international experts, initiated from a virtual scientific workshop at ACM CHI 2020. These challenges aim to coordinate future work by providing a systematic roadmap of current directions and impending hurdles to facilitate productive and effective applications for Immersive Analytics
Design Patterns for Situated Visualization in Augmented Reality
Situated visualization has become an increasingly popular research area in
the visualization community, fueled by advancements in augmented reality (AR)
technology and immersive analytics. Visualizing data in spatial proximity to
their physical referents affords new design opportunities and considerations
not present in traditional visualization, which researchers are now beginning
to explore. However, the AR research community has an extensive history of
designing graphics that are displayed in highly physical contexts. In this
work, we leverage the richness of AR research and apply it to situated
visualization. We derive design patterns which summarize common approaches of
visualizing data in situ. The design patterns are based on a survey of 293
papers published in the AR and visualization communities, as well as our own
expertise. We discuss design dimensions that help to describe both our patterns
and previous work in the literature. This discussion is accompanied by several
guidelines which explain how to apply the patterns given the constraints
imposed by the real world. We conclude by discussing future research directions
that will help establish a complete understanding of the design of situated
visualization, including the role of interactivity, tasks, and workflows.Comment: To appear in IEEE VIS 202
Spatial Interaction for Immersive Mixed-Reality Visualizations
Growing amounts of data, both in personal and professional settings, have caused an increased interest in data visualization and visual analytics.
Especially for inherently three-dimensional data, immersive technologies such as virtual and augmented reality and advanced, natural interaction techniques have been shown to facilitate data analysis.
Furthermore, in such use cases, the physical environment often plays an important role, both by directly influencing the data and by serving as context for the analysis.
Therefore, there has been a trend to bring data visualization into new, immersive environments and to make use of the physical surroundings, leading to a surge in mixed-reality visualization research.
One of the resulting challenges, however, is the design of user interaction for these often complex systems.
In my thesis, I address this challenge by investigating interaction for immersive mixed-reality visualizations regarding three core research questions:
1) What are promising types of immersive mixed-reality visualizations, and how can advanced interaction concepts be applied to them?
2) How does spatial interaction benefit these visualizations and how should such interactions be designed?
3) How can spatial interaction in these immersive environments be analyzed and evaluated?
To address the first question, I examine how various visualizations such as 3D node-link diagrams and volume visualizations can be adapted for immersive mixed-reality settings and how they stand to benefit from advanced interaction concepts.
For the second question, I study how spatial interaction in particular can help to explore data in mixed reality.
There, I look into spatial device interaction in comparison to touch input, the use of additional mobile devices as input controllers, and the potential of transparent interaction panels.
Finally, to address the third question, I present my research on how user interaction in immersive mixed-reality environments can be analyzed directly in the original, real-world locations, and how this can provide new insights.
Overall, with my research, I contribute interaction and visualization concepts, software prototypes, and findings from several user studies on how spatial interaction techniques can support the exploration of immersive mixed-reality visualizations.Zunehmende Datenmengen, sowohl im privaten als auch im beruflichen Umfeld, fĂŒhren zu einem zunehmenden Interesse an Datenvisualisierung und visueller Analyse.
Insbesondere bei inhĂ€rent dreidimensionalen Daten haben sich immersive Technologien wie Virtual und Augmented Reality sowie moderne, natĂŒrliche Interaktionstechniken als hilfreich fĂŒr die Datenanalyse erwiesen.
DarĂŒber hinaus spielt in solchen AnwendungsfĂ€llen die physische Umgebung oft eine wichtige Rolle, da sie sowohl die Daten direkt beeinflusst als auch als Kontext fĂŒr die Analyse dient.
Daher gibt es einen Trend, die Datenvisualisierung in neue, immersive Umgebungen zu bringen und die physische Umgebung zu nutzen, was zu einem Anstieg der Forschung im Bereich Mixed-Reality-Visualisierung gefĂŒhrt hat.
Eine der daraus resultierenden Herausforderungen ist jedoch die Gestaltung der Benutzerinteraktion fĂŒr diese oft komplexen Systeme.
In meiner Dissertation beschĂ€ftige ich mich mit dieser Herausforderung, indem ich die Interaktion fĂŒr immersive Mixed-Reality-Visualisierungen im Hinblick auf drei zentrale Forschungsfragen untersuche:
1) Was sind vielversprechende Arten von immersiven Mixed-Reality-Visualisierungen, und wie können fortschrittliche Interaktionskonzepte auf sie angewendet werden?
2) Wie profitieren diese Visualisierungen von rÀumlicher Interaktion und wie sollten solche Interaktionen gestaltet werden?
3) Wie kann rÀumliche Interaktion in diesen immersiven Umgebungen analysiert und ausgewertet werden?
Um die erste Frage zu beantworten, untersuche ich, wie verschiedene Visualisierungen wie 3D-Node-Link-Diagramme oder Volumenvisualisierungen fĂŒr immersive Mixed-Reality-Umgebungen angepasst werden können und wie sie von fortgeschrittenen Interaktionskonzepten profitieren.
FĂŒr die zweite Frage untersuche ich, wie insbesondere die rĂ€umliche Interaktion bei der Exploration von Daten in Mixed Reality helfen kann.
Dabei betrachte ich die Interaktion mit rÀumlichen GerÀten im Vergleich zur Touch-Eingabe, die Verwendung zusÀtzlicher mobiler GerÀte als Controller und das Potenzial transparenter Interaktionspanels.
Um die dritte Frage zu beantworten, stelle ich schlieĂlich meine Forschung darĂŒber vor, wie Benutzerinteraktion in immersiver Mixed-Reality direkt in der realen Umgebung analysiert werden kann und wie dies neue Erkenntnisse liefern kann.
Insgesamt trage ich mit meiner Forschung durch Interaktions- und Visualisierungskonzepte, Software-Prototypen und Ergebnisse aus mehreren Nutzerstudien zu der Frage bei, wie rĂ€umliche Interaktionstechniken die Erkundung von immersiven Mixed-Reality-Visualisierungen unterstĂŒtzen können
SiTAR: Situated Trajectory Analysis for In-the-Wild Pose Error Estimation
Virtual content instability caused by device pose tracking error remains a
prevalent issue in markerless augmented reality (AR), especially on smartphones
and tablets. However, when examining environments which will host AR
experiences, it is challenging to determine where those instability artifacts
will occur; we rarely have access to ground truth pose to measure pose error,
and even if pose error is available, traditional visualizations do not connect
that data with the real environment, limiting their usefulness. To address
these issues we present SiTAR (Situated Trajectory Analysis for Augmented
Reality), the first situated trajectory analysis system for AR that
incorporates estimates of pose tracking error. We start by developing the first
uncertainty-based pose error estimation method for visual-inertial simultaneous
localization and mapping (VI-SLAM), which allows us to obtain pose error
estimates without ground truth; we achieve an average accuracy of up to 96.1%
and an average F1 score of up to 0.77 in our evaluations on four VI-SLAM
datasets. Next we present our SiTAR system, implemented for ARCore devices,
combining a backend that supplies uncertainty-based pose error estimates with a
frontend that generates situated trajectory visualizations. Finally, we
evaluate the efficacy of SiTAR in realistic conditions by testing three
visualization techniques in an in-the-wild study with 15 users and 13 diverse
environments; this study reveals the impact both environment scale and the
properties of surfaces present can have on user experience and task
performance.Comment: To appear in Proceedings of IEEE ISMAR 202
Designing Situated Dashboards: Challenges and Opportunities
Situated Visualization is an emerging field that unites several areas -
visualization, augmented reality, human-computer interaction, and
internet-of-things, to support human data activities within the ubiquitous
world. Likewise, dashboards are broadly used to simplify complex data through
multiple views. However, dashboards are only adapted for desktop settings, and
requires visual strategies to support situatedness. We propose the concept of
AR-based situated dashboards and present design considerations and challenges
developed over interviews with experts. These challenges aim to propose
directions and opportunities for facilitating the effective designing and
authoring of situated dashboards.Comment: To be presented at ISA: 2nd Workshop on Immersive and Situated
Analytics @ ISMAR 202
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