PalmGesture

Wang, Chengyao; Hsiu, Min-Chieh; Chiu, Po-Tsung; Chang, Chiao-Hui; Chan, Liwei; Chen, Bing‐Yu; Chen, Mike Y.

doi:10.1145/2785830.2785885

Cited by 38 publications

(6 citation statements)

References 31 publications

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“…The surface of the palm has been used predominantly to provide a source of haptic feedback for direct touch interactions when the user is interacting with projected content [42]. The palm enables gesturing for eyes-free input [16,110]. It commonly uses the non-dominant hand's palm as an interaction surface [16,26,110], which can be used effectively for input in both conventional [16] and XR type devices [65].…”

Section: Hand / Palm (T4)mentioning

confidence: 99%

Surveying the Social Comfort of Body, Device, and Environment-Based Augmented Reality Interactions in Confined Passenger Spaces Using Mixed Reality Composite Videos

Medeiros,

Dubus,

Williamson

et al. 2023

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

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Augmented Reality (AR) headsets could significantly improve the passenger experience, freeing users from the restrictions of physical smartphones, tablets and seatback displays. However, the confined space of public transport and the varying proximity to other passengers may restrict what interaction techniques are deemed socially acceptable for AR users - particularly considering current reliance on mid-air interactions in consumer headsets. We contribute and utilize a novel approach to social acceptability video surveys, employing mixed reality composited videos to present a real user performing interactions across different virtual transport environments. This approach allows for controlled evaluation of perceived social acceptability whilst freeing researchers to present interactions in any simulated context. Our resulting survey (N=131) explores the social comfort of body, device, and environment-based interactions across seven transit seating arrangements. We reflect on the advantages of discreet inputs over mid-air and the unique challenges of face-to-face seating for passenger AR.

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Section: Hand / Palm (T4)mentioning

confidence: 99%

Surveying the Social Comfort of Body, Device, and Environment-Based Augmented Reality Interactions in Confined Passenger Spaces Using Mixed Reality Composite Videos

Medeiros,

Dubus,

Williamson

et al. 2023

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

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“…Many efforts have been devoted to identifying touch and tap events on the body surface. Some examples include locating tap on arms [20,32,45], wrist [28,29,39,62], fingers [40], fingertips [10], ears [33], and hands [18,29,49,54,57,61,62]. Harrison et al coined the term "on-body interaction" to conceptualize this line of research [19].…”

Section: Hand Location Recognitionmentioning

confidence: 99%

Hand with Sensing Sphere: Body-Centered Spatial Interactions with a Hand-Worn Spherical Camera

Arakawa

Maekawa

Kashino

et al. 2020

Symposium on Spatial User Interaction

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“…In addition to tap typing, some research investigated gesturebased text entry on touchscreen, such as an eyes-free Graffiti text input system [23,25] and a swipe-based invisible text entry method with numberpad-like layout on smartwatches [17].…”

Section: Eyes-free Text Entrymentioning

confidence: 99%

i'sFree

Zhu

Zheng

Zhai

et al. 2019

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

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Entering text without having to pay attention to the keyboard is compelling but challenging due to the lack of visual guidance. We propose i'sFree to enable eyes-free gesture typing on a distant display from a touch-enabled remote control. i'sFree does not display the keyboard or gesture trace but decodes gestures drawn on the remote control into text according to an invisible and shifting Qwerty layout. i'sFree decodes gestures similar to a general gesture typing decoder, but learns from the instantaneous and historical input gestures to dynamically adjust the keyboard location. We designed it based on the understanding of how users perform eyes-free gesture typing. Our evaluation shows eyes-free gesture typing is feasible: reducing visual guidance on the distant display hardly affects the typing speed. Results also show that the i'sFree gesture decoding algorithm is effective, enabling an input speed of 23 WPM, 46% faster than the baseline eyes-free condition built on a general gesture decoder. Finally, i'sFree is easy to learn: participants reached 22 WPM in the first ten minutes, even though 40% of them were first-time gesture typing users.

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PalmGesture

Cited by 38 publications

References 31 publications

Surveying the Social Comfort of Body, Device, and Environment-Based Augmented Reality Interactions in Confined Passenger Spaces Using Mixed Reality Composite Videos

Surveying the Social Comfort of Body, Device, and Environment-Based Augmented Reality Interactions in Confined Passenger Spaces Using Mixed Reality Composite Videos

Hand with Sensing Sphere: Body-Centered Spatial Interactions with a Hand-Worn Spherical Camera

i'sFree

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