Remote Control by Body Movement in Synchrony with Orbiting Widgets

Clarke, Christopher; Bellino, Alessio; Esteves, Augusto; Gellersen, Hans

doi:10.1145/3130910

Cited by 15 publications

(6 citation statements)

References 37 publications

(55 reference statements)

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“…Furthermore, researchers and practitioners could apply and evaluate the slope method beyond gaze, e.g. motion matching for body movements [4][5][6] and mid-air gestures [2].…”

Section: Discussion and Future Workmentioning

confidence: 99%

DialPlates

Drewes

Khamis

Alt

2019

Proceedings of the 18th International Conference on Mobile and Ubiquitous Multimedia

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In this paper we introduce a novel approach for smooth pursuits eye movement detection and demonstrate that it allows up to 160 targets to be distinguished. With this work we advance the wellestablished smooth pursuits technique, which allows gaze interaction without calibration. The approach is valuable for researchers and practitioners, since it enables novel user interfaces and applications to be created that employ a large number of targets, for example, a pursuits-based keyboard or a smart home where many different objects can be controlled using gaze. We present findings from two studies. In particular, we compare our novel detection algorithm based on linear regression with the correlation method. We quantify its accuracy for around 20 targets on a single circle and up to 160 targets on multiple circles. Finally, we implemented a pursuits-based keyboard app with 108 targets as proof-of-concept. CCS CONCEPTS • Human-centered computing → Interaction techniques.

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“…Furthermore, researchers and practitioners could apply and evaluate the slope method beyond gaze, e.g. motion matching for body movements [4][5][6] and mid-air gestures [2].…”

Section: Discussion and Future Workmentioning

confidence: 99%

DialPlates

Drewes

Khamis

Alt

2019

Proceedings of the 18th International Conference on Mobile and Ubiquitous Multimedia

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“…Researchers could investigate, how quickly users adapt to such interfaces and whether the need to strongly focus on the target decreases over time. Furthermore, researchers and practitioners could apply and evaluate the slope-based method in domains other than gaze, such as motion matching for body movements [4,5,6], and mid-air gestures [2].…”

Section: Discussionmentioning

confidence: 99%

DialPlate: Enhancing the Detection of Smooth Pursuits Eye Movements Using Linear Regression

Drewes,

Khamis,

Alt

2018

Preprint

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We introduce and evaluate a novel approach for detecting smooth pursuit eye movements that increases the number of distinguishable targets and is more robust against false positives. Being natural and calibration-free, Pursuits has been gaining popularity in the past years. At the same time, current implementations show poor performance when more than eight on-screen targets are being used, thus limiting its applicability. Our approach (1) leverages the slope of a regression line, and (2) introduces a minimum signal duration that improves both the new and the traditional detection method. After introducing the approach as well as the implementation, we compare it to the traditional correlation-based Pursuits detection method. We tested the approach up to 24 targets and show that, if accepting a similar error rate, nearly twice as many targets can be distinguished compared to state of the art. For fewer targets, accuracy increases significantly. We believe our approach will enable more robust pursuit-based user interfaces, thus making it valuable for both researchers and practitioners.

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“…Gestural interaction has been extensively studied in the literature [4,6,9,20]. However, most studies focus on performance, and there is comparatively much less work on the memorization of gestures [1,22,27].…”

Section: Related Workmentioning

confidence: 99%

How Memorizing Positions or Directions Affects Gesture Learning?

Fruchard

Lecolinet

Chapuis

2018

Proceedings of the 2018 ACM International Conference on Interactive Surfaces and Spaces

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Various techniques have been proposed to faster command selection. Many of them either rely on directional gestures (e.g. Marking menus) or pointing gestures using a spatiallystable arrangement of items (e.g. FastTap). Both types of techniques are known to leverage memorization, but not necessarily for the same reasons. In this paper, we investigate whether using directions or positions affects gesture learning. Our study shows that, while recall rates are not significantly different, participants used the novice mode more often and spent more time while learning commands with directional gestures, and they also reported more physical and mental efforts. Moreover, this study also highlights the importance of semantic relationships between gestural commands and reports on the memorization strategies that were elaborated by the participants.

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Remote Control by Body Movement in Synchrony with Orbiting Widgets

Cited by 15 publications

References 37 publications

DialPlates

DialPlates

DialPlate: Enhancing the Detection of Smooth Pursuits Eye Movements Using Linear Regression

How Memorizing Positions or Directions Affects Gesture Learning?

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