Text entry with KeyScretch

Costagliola, Gennaro; Fuccella, Vittorio; Capua, Michele Di

doi:10.1145/1943403.1943445

Cited by 13 publications

(9 citation statements)

References 23 publications

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“…These text entry methods map gestures to sequences of characters: entire words, as in Cirrin [16] and Shapewriter [14], or part of words, as in menu-augmented keyboards [9,13].…”

Section: Related Workmentioning

confidence: 99%

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Gestures and widgets

Fuccella

Isokoski

Martin

2013

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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We describe the design and evaluation of a gestural text editing technique for touchscreen devices. The gestures are drawn on top of the soft keyboard and interpreted as commands for moving the caret, performing selections, and controlling the clipboard. Our implementation is an Android service that can be used in any text editing task on Androidbased devices. We conducted an experiment to compare the gestural editing technique against the widget-based technique available on a smartphone (Samsung Galaxy II with Android 2.3.5). The results show a performance benefit of 13-24% for the gestural technique depending on the font size. Subjective feedback from the participants was also positive. Because the two editing techniques use different input areas, they can coexist on a device. This means that the gestural editing can be added on any soft keyboard without interfering with user experience for those users that choose not to use it.

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“…These text entry methods map gestures to sequences of characters: entire words, as in Cirrin [16] and Shapewriter [14], or part of words, as in menu-augmented keyboards [9,13].…”

Section: Related Workmentioning

confidence: 99%

“…Some of this work has mapped gestures drawn on the display to characters in different ways [8,9,13,14,16]. Surprisingly, the interaction techniques used for text editing have not been researched much lately.…”

Section: Introductionmentioning

confidence: 99%

Gestures and widgets

Fuccella

Isokoski

Martin

2013

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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“…by Findlater et al [6], applying extensions available through specific user gestures. Costagliola and Capua suggest implementing into the virtual keyboard an additional menu displayed upon making certain gestures around a given character [7]. Ruamviboonsuk et al suggest entering numbers sightlessly (to enable quicker dialling), using specific multi-touch combinations [8].…”

Section: Related Workmentioning

confidence: 99%

“…Ruamviboonsuk et al suggest entering numbers sightlessly (to enable quicker dialling), using specific multi-touch combinations [8]. The improvements suggested [6,7,8] have not been tested by the blind nor designed for this group of users. Southern et al suggest a fixed virtual Braille keyboard that would have 6 keys: 3 on the left and 3 on the right side of the screen, near its edges [4].…”

Section: Related Workmentioning

confidence: 99%

Linear interface for graphical interface of touch-screen

Kocielinski

Brzostek-Pawłowska

2013

Proceedings of the 15th International Conference on Human-Computer Interaction With Mobile Devices and Services

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The article presents the idea of creating a blindfriendly Versatile Multimodal Linear Interface (VMLI) model for touchscreen-based devices as well as the results of pilot study and implementation of VMLI.VMLI enhances operation of touchscreen-based mobile devices and facilitates the use of a touchscreen by the blind. VMLI transforms a planar layout of objects into hierarchically structured linear lists that allow nonsequential access to items. List items are read by VMLI using installed text-to-speech software; users navigate through lists and select items using specific touchscreen gestures preferred by the blind. VMLI allows choosing user's preferred method of text input: using a virtual QWERTY keyboard, a virtual Braille keyboard or a physical one of a Braille notetaker. The results of preliminary research on pilot implementation of VMLI into the Android system, concerning functions like managing contacts and composing messages to

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“…Some other approaches [1] also find the so called tangent vertices (smooth points separating a straight line from a curve or parting two curves). Besides stroke segmentation, the identification of corners has other applications, including gesture recognition [9] and gestural text entry [6,5].…”

Section: Introductionmentioning

confidence: 99%

RankFrag: A Machine Learning-Based Technique for Finding Corners in Hand-Drawn Digital Curves

Costagliola

Rosa

Fuccella

2015

International Conferences on Distributed Multimedia Systems

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We describe RankFrag: a technique which uses machine learning to detect corner points in hand-drawn digital curves. RankFrag classifies the stroke points by iteratively extracting them from a list of corner candidates. The points extracted in the last iterations are said to have a higher rank and are more likely to be corners. The technique has been tested on three different datasets described in the literature. We observed that, considering both accuracy and efficiency, RankFrag performs better than other state-of-art techniques.

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Text entry with KeyScretch

Cited by 13 publications

References 23 publications

Gestures and widgets

Gestures and widgets

Linear interface for graphical interface of touch-screen

RankFrag: A Machine Learning-Based Technique for Finding Corners in Hand-Drawn Digital Curves

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