Titlebook: Human-Computer Interaction – INTERACT 2021; 18th IFIP TC 13 Inte Carmelo Ardito,Rosa Lanzilotti,Kori Inkpen Conference proceedings 2021 IFI

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Philosophy and the Cambridge Apostlesf optical camera images using machine learning, and obtain reliable gesture recognition without additional sensors. We then employ an avatar to prompt users to learn and use gestures to communicate. Finally, to understand how well gestures serve as interaction methods, we compare the studied gesture

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https://doi.org/10.1057/9781137007940of dominant and non-dominant hands in tapping tasks for touch-based mobile interfaces. We set out with the expectation that throughput for a dominant digit would exceed that for the corresponding digit of the other hand. We reveal that this was followed in the case of right-handed users for both for

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Edward Lear’s Travels in Nonsense and Europe speed and highlighting with a sound guide. We measure the effect of these components on the perceived fatigue, presence, difficulty, success and helpfulness. Our findings indicate that an irregular and slow rhythm leads to a lower arm fatigue. We also find that such an irregular rhythm could increa

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https://doi.org/10.1007/978-1-349-13986-6rategies for discrete input, whereas releasing the bend is used to confirm continuous input. However, the simplest form of these strategies does not allow the rejection of unwanted or unintended input and bi-directional manipulation of the output parameter before confirming continuous input. This wo

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https://doi.org/10.1007/978-3-030-93791-1commerce). This research examines trust mechanisms based on the buyers’ perspectives in Saudi Arabia and how social platforms can be better designed to enhance trust. Two studies were conducted to achieve the aims: co-design workshops undertaken to develop and finalize design recommendations, and th

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https://doi.org/10.1007/978-1-349-00352-5s employ both vision-based and bio-sensing data to design multi-modal recognition systems. However, these approaches require tremendous domain-specific knowledge, complex pre-processing steps and fail to take full advantage of the end-to-end nature of deep learning techniques. This paper proposes a