research-article

Relative accuracy measures for stroke gestures

Authors:

Radu-Daniel Vatavu,

Jacob O. WobbrockAuthors Info & Claims

ICMI '13: Proceedings of the 15th ACM on International conference on multimodal interaction

Pages 279 - 286

https://doi.org/10.1145/2522848.2522875

Published: 09 December 2013 Publication History

Abstract

Current measures of stroke gesture articulation lack descriptive power because they only capture absolute characteristics about the gesture as a whole, not fine-grained features that reveal subtleties about the gesture articulation path. We present a set of twelve new relative accuracy measures for stroke gesture articulation that characterize the geometric, kinematic, and articulation accuracy of single and multi-stroke gestures. To compute the accuracy measures, we introduce the concept of a gesture task axis. We evaluate our measures on five public datasets comprising 38,245 samples from 107 participants, about which we make new discoveries; e.g., gestures articulated at fast speed are shorter in path length than slow or medium-speed gestures, but their path lengths vary the most, a finding that helps understand recognition performance. This work will enable a better understanding of users' stroke gesture articulation behavior, ultimately leading to better gesture set designs and more accurate recognizers.

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Cited By

Bachert MHesenius M(2024)Towards a Framework for Evaluating Synthetic Surface GesturesCompanion Proceedings of the 16th ACM SIGCHI Symposium on Engineering Interactive Computing Systems10.1145/3660515.3661327(22-30)Online publication date: 24-Jun-2024
https://dl.acm.org/doi/10.1145/3660515.3661327
Yuan LLi BWang JQu HZeng W(2024)Generating Virtual Reality Stroke Gesture Data from Out-of-Distribution Desktop Stroke Gesture Data2024 IEEE Conference Virtual Reality and 3D User Interfaces (VR)10.1109/VR58804.2024.00093(732-742)Online publication date: 16-Mar-2024
https://doi.org/10.1109/VR58804.2024.00093
Hosseini MHamidi HKermanshahani S(2024)The impacts of situational visual impairment on usability of touch screensMultimedia Tools and Applications10.1007/s11042-024-18689-983:34(81685-81709)Online publication date: 9-Mar-2024
https://doi.org/10.1007/s11042-024-18689-9
Show More Cited By

Index Terms

Relative accuracy measures for stroke gestures
1. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

cover image ACM Conferences

ICMI '13: Proceedings of the 15th ACM on International conference on multimodal interaction

December 2013

630 pages

ISBN:9781450321297

DOI:10.1145/2522848

General Chairs:
Julien Epps
The University of New South Wales, Australia
,
Fang Chen
National ICT Australia, Australia
,
Sharon Oviatt
Incaa Designs, USA
,
Kenji Mase
Nagoya University, Japan
,
Program Chairs:
Andrew Sears
Rochester Institute of Technology, USA
,
Kristiina Jokinen
University of Helsinki, Finland
,
Björn Schuller
Technische Universität München, Germany

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 December 2013

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ICMI '13

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SIGCHI

ICMI '13: 2013 International Conference on Multimodal Interaction

December 9 - 13, 2013

Sydney, Australia

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ICMI '13 Paper Acceptance Rate 49 of 133 submissions, 37%;

Overall Acceptance Rate 453 of 1,080 submissions, 42%

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Cited By

Bachert MHesenius M(2024)Towards a Framework for Evaluating Synthetic Surface GesturesCompanion Proceedings of the 16th ACM SIGCHI Symposium on Engineering Interactive Computing Systems10.1145/3660515.3661327(22-30)Online publication date: 24-Jun-2024
https://dl.acm.org/doi/10.1145/3660515.3661327
Yuan LLi BWang JQu HZeng W(2024)Generating Virtual Reality Stroke Gesture Data from Out-of-Distribution Desktop Stroke Gesture Data2024 IEEE Conference Virtual Reality and 3D User Interfaces (VR)10.1109/VR58804.2024.00093(732-742)Online publication date: 16-Mar-2024
https://doi.org/10.1109/VR58804.2024.00093
Hosseini MHamidi HKermanshahani S(2024)The impacts of situational visual impairment on usability of touch screensMultimedia Tools and Applications10.1007/s11042-024-18689-983:34(81685-81709)Online publication date: 9-Mar-2024
https://doi.org/10.1007/s11042-024-18689-9
Maslych MTaranta EAldilati MLaviola J(2023)Effective 2D Stroke-based Gesture Augmentation for RNNsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581358(1-13)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581358
Costagliola GDe Rosa MFuccella V(2023)Gesture‐Based ComputingHandbook of Human‐Machine Systems10.1002/9781119863663.ch32(397-408)Online publication date: 7-Jul-2023
https://doi.org/10.1002/9781119863663.ch32
Taranta EMaslych MGhamandi RLaViola J(2022)The Voight-Kampff Machine for Automatic Custom Gesture Rejection Threshold SelectionProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3502000(1-15)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3502000
Vatavu RUngurean O(2022)Understanding Gesture Input Articulation with Upper-Body Wearables for Users with Upper-Body Motor ImpairmentsProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3501964(1-16)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3501964
Schipor OVatavu R(2022)GearWheels: A Software Tool to Support User Experiments on Gesture Input with Wearable DevicesInternational Journal of Human–Computer Interaction10.1080/10447318.2022.209890739:18(3527-3545)Online publication date: 22-Jul-2022
https://doi.org/10.1080/10447318.2022.2098907
Terenti MVatavu R(2021)How Do HCI Researchers Describe Their Software Tools? Insights From a Synopsis Survey of Tools for Multimodal InteractionCompanion Publication of the 2021 International Conference on Multimodal Interaction10.1145/3461615.3485431(7-12)Online publication date: 18-Oct-2021
https://dl.acm.org/doi/10.1145/3461615.3485431
Kang WJung ILee DHong JKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)Styling Words: A Simple and Natural Way to Increase Variability in Training Data Collection for Gesture RecognitionProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445457(1-12)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445457
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