Augmented Reality / Interacting with Text & Notes

[A] Paper Room 15, 2021-05-12 17:00:00~2021-05-12 19:00:00 / [B] Paper Room 15, 2021-05-13 01:00:00~2021-05-13 03:00:00 / [C] Paper Room 15, 2021-05-13 09:00:00~2021-05-13 11:00:00

会議の名前
CHI 2021
A User-Oriented Approach to Space-Adaptive Augmentation: The Effects of Spatial Affordance on Narrative Experience in an Augmented Reality Detective Game
要旨

Space-adaptive algorithms aim to effectively align the virtual with the real to provide immersive user experiences for Augmented Reality(AR) content across various physical spaces. While such measures are reliant on real spatial features, efforts to understand those features from the user’s perspective and reflect them in designing adaptive augmented spaces have been lacking. For this, we compared factors of narrative experience in six spatial conditions during the gameplay of Fragments, a space-adaptive AR detective game. Configured by size and furniture layout, each condition afforded disparate degrees of traversability and visibility. Results show that whereas centered furniture clusters are suitable for higher presence in sufficiently large rooms, the same layout leads to lower narrative engagement. Based on our findings, we suggest guidelines that can enhance the effects of space adaptivity by considering how users perceive and navigate augmented space generated from different physical environments.

受賞
Honorable Mention
著者
Jae-eun Shin
KAIST, Daejeon, Korea, Republic of
Boram Yoon
UVR Lab, KAIST, Daejeon, Korea, Republic of
Dooyoung Kim
KAIST, Daejeon, Korea, Republic of
Woontack Woo
KAIST , Daejeon, Korea, Republic of
DOI

10.1145/3411764.3445675

論文URL

https://doi.org/10.1145/3411764.3445675

動画
Augmented Reality and Older Adults: A Comparison of Prompting Types
要旨

Older adults can benefit from technologies that help them to complete everyday tasks. However, they are an often-under-represented population in augmented reality (AR) research. We present the results of a study in which people aged 50 years or older were asked to perform actions by interpreting visual AR prompts in a lab setting. Our results show that users were less successful at completing actions when using ARROW and HIGHLIGHT augmentations than when using ghosted OBJECT or GHOSTHAND augmentations. We found that user confidence in performing actions varied according to action and augmentation type. Users preferred combined AUDIO+TEXT prompts (our control condition) overall, but the GHOSTHAND was the most preferred visual prompt. We discuss reasons for these differences and provide insight for developers of AR content for older adults. Our work provides the first comparative study of AR with older adults in a non-industrial context.

受賞
Honorable Mention
著者
Thomas J.. Williams
University of Bath, Bath, United Kingdom
Simon L.. Jones
University of Bath, Bath, United Kingdom
Christof Lutteroth
University of Bath, Bath, United Kingdom
Elies Dekoninck
University of Bath, Bath, United Kingdom
Hazel C. Boyd
Designability, Bath, United Kingdom
DOI

10.1145/3411764.3445476

論文URL

https://doi.org/10.1145/3411764.3445476

動画
"I Can't Reply with That": Characterizing Problematic Email Reply Suggestions
要旨

In email interfaces, providing users with reply suggestions may simplify or accelerate correspondence. While the "success" of such systems is typically quantified using the number of suggestions selected by users, this ignores the impact of social context, which can change how suggestions are perceived. To address this, we developed a mixed-methods framework involving qualitative interviews and crowdsourced experiments to characterize problematic email reply suggestions. Our interviews revealed issues with over-positive, dissonant, cultural, and gender-assuming replies, as well as contextual politeness. In our experiments, crowdworkers assessed email scenarios that we generated and systematically controlled, showing that contextual factors like social ties and the presence of salutations impacts users' perceptions of email correspondence. These assessments created a novel dataset of human-authored corrections for problematic email replies. Our study highlights the social complexity of providing suggestions for email correspondence, raising issues that may apply to all social messaging systems.

著者
Ronald E. Robertson
Northeastern University, Boston, Massachusetts, United States
Alexandra Olteanu
Microsoft Research, NY, New York, United States
Fernando Diaz
Microsoft Research, Montreal, Quebec, Canada
Milad Shokouhi
Microsoft, Redmond, Washington, United States
Peter Bailey
Microsoft, Canberra, Australia
DOI

10.1145/3411764.3445557

論文URL

https://doi.org/10.1145/3411764.3445557

動画
Enhancing the Composition Task in Text Entry Studies: Eliciting Difficult Text and Improving Error Rate Calculation
要旨

Participants in text entry studies usually copy phrases or compose novel messages. A composition task mimics actual user behavior and can allow researchers to better understand how a system might perform in reality. A problem with composition is that participants may gravitate towards writing simple text, that is, text containing only common words. Such simple text is insufficient to explore all factors governing a text entry method, such as its error correction features. We contribute to enhancing composition tasks in two ways. First, we show participants can modulate the difficulty of their compositions based on simple instructions. While it took more time to compose difficult messages, they were longer, had more difficult words, and resulted in more use of error correction features. Second, we compare two methods for obtaining a participant's intended text, comparing both methods with a previously proposed crowdsourced judging procedure. We found participant-supplied references were more accurate.

著者
Dylan Gaines
Michigan Technological University, Houghton, Michigan, United States
Per Ola Kristensson
University of Cambridge, Cambridge, United Kingdom
Keith Vertanen
Michigan Technological University, Houghton, Michigan, United States
DOI

10.1145/3411764.3445199

論文URL

https://doi.org/10.1145/3411764.3445199

動画
CoNotate: Suggesting Queries Based on Notes Promotes Knowledge Discovery
要旨

When exploring a new domain through web search, people often struggle to articulate queries because they lack domain-specific language and well-defined informational goals. Perhaps search tools rely too much on the query to understand what a searcher wants. Towards expanding this contextual understanding of a user during exploratory search, we introduce a novel system, CoNotate, which offers query suggestions based on analyzing the searcher's notes and previous searches for patterns and gaps in information. To evaluate this approach, we conducted a within-subjects study where participants (n=38) conducted exploratory searches using a baseline system (standard web search) and the CoNotate system. The CoNotate approach helped searchers issue significantly more queries, and discover more terminology than standard web search. This work demonstrates how search can leverage user-generated content to help people get started when exploring complex, multi-faceted information spaces.

著者
Srishti Palani
University of California, San Diego, California, United States
Zijian Ding
University of California, San Diego, California, United States
Austin Nguyen
University of California, San Diego, California, United States
Andrew Chuang
University of California, San Diego, California, United States
Stephen MacNeil
University of California, San Diego, California, United States
Steven P.. Dow
University of California, San Diego, California, United States
DOI

10.1145/3411764.3445618

論文URL

https://doi.org/10.1145/3411764.3445618

動画
ToonNote: Improving Communication in Computational Notebooks Using Interactive Data Comics
要旨

Computational notebooks help data analysts analyze and visualize datasets, and share analysis procedures and outputs. However, notebooks typically combine code (e.g., Python scripts), notes, and outputs (e.g., tables, graphs). The combination of disparate materials is known to hinder the comprehension of notebooks, making it difficult for analysts to collaborate with other analysts unfamiliar with the dataset. To mitigate this problem, we introduce ToonNote, a JupyterLab extension that enables the conversion of notebooks into "data comics.'' ToonNote provides a simplified view of a Jupyter notebook, highlighting the most important results while supporting interactive and free exploration of the dataset. This paper presents the results of a formative study that motivated the system, its implementation, and an evaluation with 12 users, demonstrating the effectiveness of the produced comics. We discuss how our findings inform the future design of interfaces for computational notebooks and features to support diverse collaborators.

著者
DaYe Kang
KAIST, Deajeon, Korea, Republic of
Tony Ho
Simon Fraser University, Burnaby, British Columbia, Canada
Nicolai Marquardt
University College London, London, United Kingdom
Bilge Mutlu
University of Wisconsin-Madison, Madison, Wisconsin, United States
Andrea Bianchi
KAIST, Daejeon, Korea, Republic of
DOI

10.1145/3411764.3445434

論文URL

https://doi.org/10.1145/3411764.3445434

動画
Assisting Manipulation and Grasping in Robot Teleoperation with Augmented Reality Visual Cues
要旨

Teleoperating industrial manipulators in co-located spaces can be challenging. Facilitating robot teleoperation by providing additional visual information about the environment and the robot affordances using augmented reality (AR), can improve task performance in manipulation and grasping. In this paper, we present two designs of augmented visual cues, that aim to enhance the visual space of the robot operator through hints about the position of the robot gripper in the workspace and in relation to the target. These visual cues aim to improve the distance perception and thus, the task performance. We evaluate both designs against a baseline in an experiment where participants teleoperate a robotic arm to perform pick-and-place tasks. Our results show performance improvements in different levels, reflecting in objective and subjective measures with trade-offs in terms of time, accuracy, and participants' views of teleoperation. These findings show the potential of AR not only in teleoperation, but in understanding the human-robot workspace.

著者
Stephanie Arevalo Arboleda
Westphalian University of Applied Sciences, Gelsenkirchen, Germany
Franziska Rücker
Westphalian University of Applied Sciences, Gelsenkirchen, Germany
Tim Dierks
Westphalian University of Applied Sciences, Gelsenkirchen, NRW, Germany
Jens Gerken
Westphalian University of Applied Sciences, Gelsenkirchen, Germany
DOI

10.1145/3411764.3445398

論文URL

https://doi.org/10.1145/3411764.3445398

動画
Augmented Reality Glasses as an Orientation and Mobility Aid for People with Low Vision: a Feasibility Study of Experiences and Requirements
要旨

People with low vision experience reduced mobility that affects their physical and mental wellbeing. With augmented reality (AR) glasses, there are new opportunities to provide visual and auditory information that can improve mobility for this vulnerable group. Current research into AR-based mobility aids has focused mainly on the technical aspects, and less emphasis has been placed on understanding the usability and suitability of these aids in people with various levels of visual impairment. In this paper, we present the results of qualitative interviews with 18 participants using HoloLens v1 and eight prototype augmentations to understand how these enhancements are perceived by people with low vision and how these aids should be adjusted to suit their needs. Our results suggested that participants with moderate vision loss could potentially perceive the most benefit from glasses and underlined the importance of extensive customizability to accommodate the needs of a highly varied low vision population.

著者
Hein Min Htike
Cardiff University, Cardiff, United Kingdom
Tom H. Margrain
Cardiff University, Cardiff, United Kingdom
Yu-Kun Lai
Cardiff University, Cardiff, Wales, United Kingdom
Parisa Eslambolchilar
Cardiff University, Cardiff, Wales, United Kingdom
DOI

10.1145/3411764.3445327

論文URL

https://doi.org/10.1145/3411764.3445327

動画
Exploring Augmented Visual Alterations in Interpersonal Communication
要旨

Augmented Reality (AR) glasses equip users with the tools to modify the visual appearance of their surrounding environment. This might severely impact interpersonal communication, as the conversational partners will no longer share the same visual perception of reality. Grounded in color-in-context theory, we present a potential AR application scenario in which users can modify the color of the environment to achieve subconscious benefits. In a consecutive online survey (N=64), we measured the user's comfort, acceptance of altering and being altered, and how it is impacted by being able to perceive or not perceive the alteration. We identified significant differences depending on (1) who or what is the target of the alteration, (2) which body part is altered, and (3) which relationship the conversational partners share. In light of our quantitative and qualitative findings, we discuss ethical and practical implications for future devices and applications that employ visual alterations.

著者
Jan Ole Rixen
Institute of Media Informatics, Ulm, Germany
Teresa Hirzle
Ulm University, Ulm, Germany
Mark Colley
Ulm University, Ulm, Germany
Yannick Etzel
Institute of Media Informatics, Ulm, Germany
Enrico Rukzio
University of Ulm, Ulm, Germany
Jan Gugenheimer
Institut Polytechnique de Paris, Paris, France
DOI

10.1145/3411764.3445597

論文URL

https://doi.org/10.1145/3411764.3445597

動画
Crowdsourcing Design Guidance for Contextual Adaptation of Text Content in Augmented Reality
要旨

Augmented Reality (AR) can deliver engaging user experiences that seamlessly meld virtual content with the physical environment. However, building such experiences is challenging due to the developer’s inability to assess how uncontrolled deployment contexts may influence the user experience. To address this issue, we demonstrate a method for rapidly conducting AR experiments and real-world data collection in the user's own physical environment using a privacy-conscious mobile web application. The approach leverages the large number of distinct user contexts accessible through crowdsourcing to efficiently source diverse context and perceptual preference data. The insights gathered through this method complement emerging design guidance and sample-limited lab-based studies. The utility of the method is illustrated by re-examining the design challenge of adapting AR text content to the user's environment. Finally, we demonstrate how gathered design insight can be operationalized to provide adaptive text content functionality in an AR headset.

著者
John J. Dudley
University of Cambridge, Cambridge, United Kingdom
Jason T.. Jacques
University of Cambridge, Cambridge, United Kingdom
Per Ola Kristensson
University of Cambridge, Cambridge, United Kingdom
DOI

10.1145/3411764.3445493

論文URL

https://doi.org/10.1145/3411764.3445493

動画
The Impact of Multiple Parallel Phrase Suggestions on Email Input and Composition Behaviour of Native and Non-Native English Writers
要旨

We present an in-depth analysis of the impact of multi-word suggestion choices from a neural language model on user behaviour regarding input and text composition in email writing. Our study for the first time compares different numbers of parallel suggestions, and use by native and non-native English writers, to explore a trade-off of ``efficiency vs ideation'', emerging from recent literature. We built a text editor prototype with a neural language model (GPT-2), refined in a prestudy with 30 people. In an online study (N=156), people composed emails in four conditions (0/1/3/6 parallel suggestions). Our results reveal (1) benefits for ideation, and costs for efficiency, when suggesting multiple phrases; (2) that non-native speakers benefit more from more suggestions; and (3) further insights into behaviour patterns. We discuss implications for research, the design of interactive suggestion systems, and the vision of supporting writers with AI instead of replacing them.

受賞
Honorable Mention
著者
Daniel Buschek
University of Bayreuth, Bayreuth, Germany
Martin Zürn
LMU Munich, Munich, Germany
Malin Eiband
LMU Munich, Munich, Germany
DOI

10.1145/3411764.3445372

論文URL

https://doi.org/10.1145/3411764.3445372

動画
Adaptive Subtitles: Preferences and Trade-Offs in Real-Time Media Adaption
要旨

Subtitles can help improve the understanding of media content. People enable subtitles based on individual characteristics (e.g., language or hearing ability), viewing environment, or media context (e.g., drama, quiz show). However, some people find that subtitles can be distracting and that they negatively impact their viewing experience. We explore the challenges and opportunities surrounding interaction with real-time personalisation of subtitled content. To understand how people currently interact with subtitles, we first conducted an online questionnaire with 102 participants. We used our findings to elicit requirements for a new approach called Adaptive Subtitles that allows the viewer to alter which speakers have subtitles displayed in real-time. We evaluated our approach with 19 participants to understand the interaction trade-offs and challenges within real-time adaptations of subtitled media. Our evaluation findings suggest that granular controls and structured onboarding allow viewers to make informed trade-offs when adapting media content, leading to improved viewing experiences.

著者
Benjamin M.. Gorman
Bournemouth University, Bournemouth, Dorset, United Kingdom
Michael Crabb
University of Dundee, Dundee, Dundee, United Kingdom
Michael Armstrong
BBC Research and Development, Salford, Manchester, United Kingdom
DOI

10.1145/3411764.3445509

論文URL

https://doi.org/10.1145/3411764.3445509

動画