research-article

Motion Correlation: Selecting Objects by Matching Their Movement

Authors:

Eduardo Velloso,

Augusto Esteves,

Christopher Clarke,

Hans GellersenAuthors Info & Claims

ACM Transactions on Computer-Human Interaction (TOCHI), Volume 24, Issue 3

Article No.: 22, Pages 1 - 35

https://doi.org/10.1145/3064937

Published: 28 April 2017 Publication History

Abstract

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.

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Cited By

Hou BNewn JSidenmark LKhan AGellersen H(2024)GazeSwitch: Automatic Eye-Head Mode Switching for Optimised Hands-Free PointingProceedings of the ACM on Human-Computer Interaction10.1145/36556018:ETRA(1-20)Online publication date: 28-May-2024
https://dl.acm.org/doi/10.1145/3655601
Carneiro ACoutinho FMorimoto C(2024)Detection of visual pursuits using 1D convolutional neural networksPattern Recognition Letters10.1016/j.patrec.2024.01.020179:C(45-51)Online publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1016/j.patrec.2024.01.020
Yi-yan WWen CJing-ze TWei-chi HYa-feng NWen-jun YCheng-qi X(2024)Design recommendations of target size and tracking speed under circular and square trajectories for smooth pursuit with Euclidean algorithm in eye-control systemDisplays10.1016/j.displa.2023.10260881(102608)Online publication date: Jan-2024
https://doi.org/10.1016/j.displa.2023.102608
Show More Cited By

Index Terms

Motion Correlation: Selecting Objects by Matching Their Movement
1. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Transactions on Computer-Human Interaction

ACM Transactions on Computer-Human Interaction Volume 24, Issue 3

June 2017

244 pages

ISSN:1073-0516

EISSN:1557-7325

DOI:10.1145/3086563

Editor:
Ken Hinckley
Microsoft Research

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Copyright © 2017 ACM.

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Publication History

Published: 28 April 2017

Accepted: 01 March 2017

Revised: 01 February 2017

Received: 01 August 2016

Published in TOCHI Volume 24, Issue 3

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Google through a Faculty Research Award
Microsoft Research Centre for Social Natural User Interfaces (SocialNUI)

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Cited By

Hou BNewn JSidenmark LKhan AGellersen H(2024)GazeSwitch: Automatic Eye-Head Mode Switching for Optimised Hands-Free PointingProceedings of the ACM on Human-Computer Interaction10.1145/36556018:ETRA(1-20)Online publication date: 28-May-2024
https://dl.acm.org/doi/10.1145/3655601
Carneiro ACoutinho FMorimoto C(2024)Detection of visual pursuits using 1D convolutional neural networksPattern Recognition Letters10.1016/j.patrec.2024.01.020179:C(45-51)Online publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1016/j.patrec.2024.01.020
Yi-yan WWen CJing-ze TWei-chi HYa-feng NWen-jun YCheng-qi X(2024)Design recommendations of target size and tracking speed under circular and square trajectories for smooth pursuit with Euclidean algorithm in eye-control systemDisplays10.1016/j.displa.2023.10260881(102608)Online publication date: Jan-2024
https://doi.org/10.1016/j.displa.2023.102608
Wang YTian JXiao LHe JNiu Y(2024)Research on a spatial–temporal characterisation of blink-triggered eye control interactionsAdvanced Engineering Informatics10.1016/j.aei.2023.10229759(102297)Online publication date: Jan-2024
https://doi.org/10.1016/j.aei.2023.102297
Bellino ARocchesso D(2024)SoundOrbit: motion-correlation interaction with auditory orbital trajectoriesPersonal and Ubiquitous Computing10.1007/s00779-024-01818-4Online publication date: 15-Jun-2024
https://doi.org/10.1007/s00779-024-01818-4
Waugh KMcGill MFreeman E(2023)Proxemic Cursor Interactions for Touchless Widget ControlProceedings of the 2023 ACM Symposium on Spatial User Interaction10.1145/3607822.3614525(1-12)Online publication date: 13-Oct-2023
https://dl.acm.org/doi/10.1145/3607822.3614525
Lei YHe SKhamis MYe J(2023)An End-to-End Review of Gaze Estimation and its Interactive Applications on Handheld Mobile DevicesACM Computing Surveys10.1145/360694756:2(1-38)Online publication date: 15-Sep-2023
https://dl.acm.org/doi/10.1145/3606947
Namnakani OSinrattanavong PAbdrabou YBulling AAlt FKhamis M(2023)GazeCast: Using Mobile Devices to Allow Gaze-based Interaction on Public DisplaysProceedings of the 2023 Symposium on Eye Tracking Research and Applications10.1145/3588015.3589663(1-8)Online publication date: 30-May-2023
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Namnakani OAbdrabou YGrizou JEsteves AKhamis M(2023)Comparing Dwell time, Pursuits and Gaze Gestures for Gaze Interaction on Handheld Mobile DevicesProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580871(1-17)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580871
Sidenmark LClarke CNewn JLystbæk MPfeuffer KGellersen H(2023)Vergence Matching: Inferring Attention to Objects in 3D Environments for Gaze-Assisted SelectionProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580685(1-15)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580685
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