User-Driven Design Principles for Gesture Representations

McAweeney, Erin; Zhang, Haihua; Nebeling, Michael

doi:10.1145/3173574.3174121

Cited by 21 publications

(44 citation statements)

References 33 publications

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“…The touch area indicates the command trigger area, e.g., two fingers quickly tap anywhere on the ear to trigger "pause" or one finger tap the ear tragus for an "act on selection" task. Note that all gesture representations meet the user-driven design principles which were presented by McAweeney et al [21].…”

Section: Agreement Between Participantsmentioning

confidence: 96%

“…This gesture set is a non-oneto-one mapping of tasks and gestures. To illustrate precisely the gestures, we followed the design principles for gesture representations which were presented by McAweeney et al [21]. In addition, despite there being no consensus for "voice search" (AR = .093) or "turn on the microphone" (AR = .098), we still provided the gesture which comprised a relative majority and marked these with a star to distinguish this quality.…”

Section: 23mentioning

confidence: 99%

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Exploring User Defined Gestures for Ear-Based Interactions

Chen

Liao

Hsu

et al. 2020

Proc. ACM Hum.-Comput. Interact.

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The human ear is highly sensitive and accessible, making it especially suitable for being used as an interface for interacting with smart earpieces or augmented glasses. However, previous works on ear-based input mainly address gesture sensing technology and researcher-designed gestures. This paper aims to bring more understandings of gesture design. Thus, for a user elicitation study, we recruited 28 participants, each of whom designed gestures for 31 smart device-related tasks. This resulted in a total of 868 gestures generated. Upon the basis of these gestures, we compiled a taxonomy and concluded the considerations underlying the participants' designs that also offer insights into their design rationales and preferences. Thereafter, based on these study results, we propose a set of user-defined gestures and share interesting findings. We hope this work can shed some light on not only sensing technologies of ear-based input, but also the interface design of future wearable interfaces. CCS Concepts: • Human-centered computing → Gestural input; User studies.

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Section: Agreement Between Participantsmentioning

confidence: 96%

Section: 23mentioning

confidence: 99%

Exploring User Defined Gestures for Ear-Based Interactions

Chen

Liao

Hsu

et al. 2020

Proc. ACM Hum.-Comput. Interact.

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show abstract

“…Referent presentation. As prior work shows that elicitation studies have used various referent formats (e.g., text [2], videos [24]), it is important to maximize referentpresentation flexibility for researchers by allowing them to choose from different formats.…”

Section: Crowdlicit Requirements the Requirements R1-r6mentioning

confidence: 99%

Crowdlicit

Ali

Morris

Wobbrock

2019

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

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End-user elicitation studies are a popular design method. Currently, such studies are usually confined to a lab, limiting the number and diversity of participants, and therefore the representativeness of their results. Furthermore, the quality of the results from such studies generally lacks any formal means of evaluation. In this paper, we address some of the limitations of elicitation studies through the creation of the Crowdlicit system along with the introduction of end-user identification studies, which are the reverse of elicitation studies. Crowdlicit is a new web-based system that enables researchers to conduct online and in-lab elicitation and identification studies. We used Crowdlicit to run a crowd-powered elicitation study based on Morris's "Web on the Wall" study (2012) with 78 participants, arriving at a set of symbols that included six new symbols different from Morris's. We evaluated the effectiveness of 49 symbols (43 from Morris and six from Crowdlicit) by conducting a crowd-powered identification study. We show that the Crowdlicit elicitation study resulted in a set of symbols that was significantly more identifiable than Morris's. CCS CONCEPTS • Human-centered computing → HCI design and evaluation methods KEYWORDS End-user elicitation study; end-user identification study; user-driven design; crowdsourcing; Mechanical Turk.

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“…2. Overview of system setup or assembly (26): these illustrations show, for example, the setup of tracking cameras, the setup of hardware (e.g., [9, fig 1d]) or the technical assembly of a wearable device. 3.…”

Section: Taxonomy Of Trace Figuresmentioning

confidence: 99%

Esquisse: Using 3D Models Staging to Facilitate the Creation of Vector-Based Trace Figures

Antoine

Malacria

Marquardt

et al. 2019

Human-Computer Interaction – INTERACT 2019

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Trace figures are contour drawings of people and objects that capture the essence of scenes without the visual noise of photos or other visual representations. Their focus and clarity make them ideal representations to illustrate designs or interaction techniques. In practice, creating those figures is a tedious task requiring advanced skills, even when creating the figures by tracing outlines based on photos. To mediate the process of creating trace figures, we introduce the open-source tool Esquisse. Informed by our taxonomy of 124 trace figures, Esquisse provides an innovative 3D model staging workflow, with specific interaction techniques that facilitate 3D staging through kinematic manipulation, anchor points and posture tracking. Our rendering algorithm (including stroboscopic rendering effects) creates vector-based trace figures of 3D scenes. We validated Esquisse with an experiment where participants created trace figures illustrating interaction techniques, and results show that participants quickly managed to use and appropriate the tool.

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User-Driven Design Principles for Gesture Representations

Cited by 21 publications

References 33 publications

Exploring User Defined Gestures for Ear-Based Interactions

Exploring User Defined Gestures for Ear-Based Interactions

Crowdlicit

Esquisse: Using 3D Models Staging to Facilitate the Creation of Vector-Based Trace Figures

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