Exploring at-your-side gestural interaction for ubiquitous environments
Proceedings of the 2017 Conference on Designing Interactive Systems, 2017•dl.acm.org
Free-space gestural systems are faced with two major issues: a lack of subtlety due to
explicit mid-air arm movements, and the highly effortful nature of such interactions. With an
ever-growing ubiquity of interactive devices, displays, and appliances with non-standard
interfaces, lower-effort and more socially acceptable interaction paradigms are essential. To
address these issues, we explore at-one's-side gestural input. Within this space, we present
the results of two studies that investigate the use of side-gesture input for interaction. First …
explicit mid-air arm movements, and the highly effortful nature of such interactions. With an
ever-growing ubiquity of interactive devices, displays, and appliances with non-standard
interfaces, lower-effort and more socially acceptable interaction paradigms are essential. To
address these issues, we explore at-one's-side gestural input. Within this space, we present
the results of two studies that investigate the use of side-gesture input for interaction. First …
Free-space gestural systems are faced with two major issues: a lack of subtlety due to explicit mid-air arm movements, and the highly effortful nature of such interactions. With an ever-growing ubiquity of interactive devices, displays, and appliances with non-standard interfaces, lower-effort and more socially acceptable interaction paradigms are essential. To address these issues, we explore at-one's-side gestural input. Within this space, we present the results of two studies that investigate the use of side-gesture input for interaction. First, we investigate end-user preference through a gesture elicitation study, present a gesture set, and validate the need for dynamic, diverse, and variable-length gestures. We then explore the feasibility of designing such a gesture recognition system, dubbed WatchTrace, which supports alphanumeric gestures of up to length three with an average accuracy of up to 82%, providing a rich, dynamic, and feasible gestural vocabulary.
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