EyeScout

Khamis, Mohamed; Hoesl, Axel; Klimczak, A.; Reiss, Martin A.; Alt, Florian; Bulling, Andreas

doi:10.1145/3126594.3126630

Cited by 42 publications

(17 citation statements)

References 40 publications

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“…Apart from implicit interaction, a large body of work investigated explicit input through modalities beyond keys and buttons, such as touch [13], mid-air gestures [14], feet-input [15], mobile devices [16], eye gaze [17], or multi-modal combinations of them [18].…”

Section: Interacting With Public Displaysmentioning

confidence: 99%

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Predicting mid-air gestural interaction with public displays based on audience behaviour

Gentile

Khamis

Milazzo

et al. 2020

International Journal of Human-Computer Studies

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Knowledge about the expected interaction duration and expected distance from which users will interact with public displays can be useful in many ways. For example, knowing upfront that a certain setup will lead to shorter interactions can nudge space owners to alter the setup. If a system can predict that incoming users will interact at a long distance for a short amount of time, it can accordingly show shorter versions of content (e.g., videos/advertisements) and employ at-a-distance interaction modalities (e.g., mid-air gestures). In this work, we propose a method to build models for predicting users' interaction duration and distance in public display environments, focusing on mid-air gestural interactive displays. First, we report our findings from a field study showing that multiple variables, such as audience size and behaviour, significantly influence interaction duration and distance. We then train predictor models using contextual data, based on the same variables. By applying our method to a mid-air gestural interactive public display deployment, we build a model that predicts interaction duration with an average error of about 8 s, and interaction distance with an average error of about 35 cm. We discuss how researchers and practitioners can use our work to build their own predictor models, and how they can use them to optimise their deployment.

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Section: Interacting With Public Displaysmentioning

confidence: 99%

“…Interaction distances are governed by the range of the cameras used for tracking the eyes. With the exception of active eye-tracking systems [17], most commercial eye trackers require users to position themselves 60cm-90cm away from the display [27].…”

Section: Touchless Interactionmentioning

confidence: 99%

Predicting mid-air gestural interaction with public displays based on audience behaviour

Gentile

Khamis

Milazzo

et al. 2020

International Journal of Human-Computer Studies

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“…Pervasive eye tracking has also become part of everyday life, found in gaze controlled computer games [53] and fatigue detection systems in cars [15]. Pervasive eye tracking can be conducted with web cams [41], smart-phone cameras [24], head-mounted eye trackers [26], with cameras installed in the environment [49], or below public displays [27]. Mobile eye trackers (such as the one used here) also enable hands-free interaction that allows users to focus on their surroundings.…”

Section: Pervasive Eye Tracking and Eye-based Interactionmentioning

confidence: 99%

Gaze-Guided Narratives

Kwok

Kiefer

Schinazi

et al. 2019

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

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“…Similar to Gaze, Multimodal suffered from the small interaction area, as users had to position themselves carefully. As sensing technologies continue to advance [12], Multimodal has a high potential to be a very fast technique, as even in its current form its performance was comparable to Touch.…”

Section: Multimodalmentioning

confidence: 99%

Pocket Transfers

Mäkelä

Khamis

Mecke

et al. 2018

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

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We present Pocket Transfers: interaction techniques that allow users to transfer content from situated displays to a personal mobile device while keeping the device in a pocket or bag. Existing content transfer solutions require direct manipulation of the mobile device, making interaction slower and less flexible. Our introduced techniques employ touch, midair gestures, gaze, and a multimodal combination of gaze and mid-air gestures. We evaluated the techniques in a novel user study (N=20), where we considered dynamic scenarios where the user approaches the display, completes the task, and leaves. We show that all pocket transfer techniques are fast and seen as highly convenient. Mid-air gestures are the most efficient touchless method for transferring a single item, while the multimodal method is the fastest touchless method when multiple items are transferred. We provide guidelines to help researchers and practitioners choose the most suitable content transfer techniques for their systems.

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EyeScout

Abstract: There may be differences between this version and the published version. You are advised to consult the publisher's version if you wish to cite from it.

Cited by 42 publications

References 40 publications

Predicting mid-air gestural interaction with public displays based on audience behaviour

Predicting mid-air gestural interaction with public displays based on audience behaviour

Gaze-Guided Narratives

Pocket Transfers

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