Rights statement: c 2017 ACM This is the author’s version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Computer-Human Interaction, 24, 3 2017 http://doi.acm.org/10.1145/3064937
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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Motion Correlation: Selecting Objects by Matching Their Movement
T2 - Selecting Objects by Matching Their Movement
AU - Velloso, Eduardo
AU - Carter, Marcus
AU - Newn, Joshua
AU - Abreu Esteves, Augusto Emanuel
AU - Clarke, Christopher
AU - Gellersen, Hans-Werner Georg
N1 - c 2017 ACM This is the author’s version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Computer-Human Interaction, 24, 3 2017 http://doi.acm.org/10.1145/3064937
PY - 2017/7/22
Y1 - 2017/7/22
N2 - Selection is a canonical task in user interfaces, commonly supported by presenting objects for acquisition by pointing. In this article, we consider motion correlation as an alternative for selection. The principle is to represent available objects by motion in the interface, have users identify a target by mimicking its specific motion, and use the correlation between the system’s output with the user’s input to determine the selection. The resulting interaction has compelling properties, as users are guided by motion feedback, and only need to copy a presented motion. Motion correlation has been explored in earlier work but only recently begun to feature in holistic interface designs. We provide a first comprehensive review of the principle, and present an analysis of five previously published works, in which motion correlation underpinned the design of novel gaze and gesture interfaces for diverse application contexts. We derive guidelines for motion correlation algorithms, motion feedback, choice of modalities, overall design of motion correlation interfaces, and identify opportunities and challenges identified for future research and design.
AB - Selection is a canonical task in user interfaces, commonly supported by presenting objects for acquisition by pointing. In this article, we consider motion correlation as an alternative for selection. The principle is to represent available objects by motion in the interface, have users identify a target by mimicking its specific motion, and use the correlation between the system’s output with the user’s input to determine the selection. The resulting interaction has compelling properties, as users are guided by motion feedback, and only need to copy a presented motion. Motion correlation has been explored in earlier work but only recently begun to feature in holistic interface designs. We provide a first comprehensive review of the principle, and present an analysis of five previously published works, in which motion correlation underpinned the design of novel gaze and gesture interfaces for diverse application contexts. We derive guidelines for motion correlation algorithms, motion feedback, choice of modalities, overall design of motion correlation interfaces, and identify opportunities and challenges identified for future research and design.
U2 - 10.1145/3064937
DO - 10.1145/3064937
M3 - Journal article
VL - 24
JO - ACM Transactions on Computer-Human Interaction (TOCHI)
JF - ACM Transactions on Computer-Human Interaction (TOCHI)
SN - 1073-0516
IS - 3
M1 - 22
ER -