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IrotateGrasp: automatic screen rotation based on grasp of mobile devices

Published: 27 April 2013 Publication History

Abstract

Automatic screen rotation improves viewing experience and usability of mobile devices, but current gravity-based approaches do not support postures such as lying on one side, and manual rotation switches require explicit user input. iRotateGrasp automatically rotates screens of mobile devices to match users' viewing orientations based on how users are grasping the devices. Our insight is that users' grasps are consistent for each orientation, but significantly differ between different orientations. Our prototype used a total of 44 capacitive sensors along the four sides and the back of an iPod Touch, and uses support vector machine (SVM) to recognize grasps at 25Hz. We collected 6-users' usage under 108 different combinations of posture, orienta-tion, touchscreen operation, and left/right/both hands. Our offline analysis showed that our grasp-based approach is promising, with 80.9% accuracy when training and testing on different users, and up to 96.7% if users are willing to train the system. Our user study (N=16) showed that iRo-tateGrasp had an accuracy of 78.8% and was 31.3% more accurate than gravity-based rotation.

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Cited By

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  • (2022)Quick Screen View Rotation based on Device Rotation Prediction by SVM2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)10.1109/GCCE56475.2022.10014241(666-667)Online publication date: 18-Oct-2022
  • (2021)Auth+Track: Enabling Authentication Free Interaction on Smartphone by Continuous User TrackingProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445624(1-16)Online publication date: 6-May-2021
  • (2019)Expanding One-Handed Touch Input Vocabulary Using Index Finger on and Above Back-of-DeviceProceedings of the 31st Australian Conference on Human-Computer-Interaction10.1145/3369457.3369537(585-589)Online publication date: 2-Dec-2019
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    cover image ACM Conferences
    CHI '13: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
    April 2013
    3550 pages
    ISBN:9781450318990
    DOI:10.1145/2470654
    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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    Published: 27 April 2013

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    Author Tags

    1. adaptive user interface
    2. auto rotation
    3. device orientation
    4. grasp recognition
    5. mobile device

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    CHI '13 Paper Acceptance Rate 392 of 1,963 submissions, 20%;
    Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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    Cited By

    View all
    • (2022)Quick Screen View Rotation based on Device Rotation Prediction by SVM2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)10.1109/GCCE56475.2022.10014241(666-667)Online publication date: 18-Oct-2022
    • (2021)Auth+Track: Enabling Authentication Free Interaction on Smartphone by Continuous User TrackingProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445624(1-16)Online publication date: 6-May-2021
    • (2019)Expanding One-Handed Touch Input Vocabulary Using Index Finger on and Above Back-of-DeviceProceedings of the 31st Australian Conference on Human-Computer-Interaction10.1145/3369457.3369537(585-589)Online publication date: 2-Dec-2019
    • (2019)HandSeeProceedings of the 2019 CHI Conference on Human Factors in Computing Systems10.1145/3290605.3300935(1-13)Online publication date: 2-May-2019
    • (2019)Active EdgeProceedings of the 2019 CHI Conference on Human Factors in Computing Systems10.1145/3290605.3300504(1-13)Online publication date: 2-May-2019
    • (2019)Sensing Posture-Aware Pen+Touch Interaction on TabletsProceedings of the 2019 CHI Conference on Human Factors in Computing Systems10.1145/3290605.3300285(1-14)Online publication date: 2-May-2019
    • (2019)SmartGrip: grip sensing system for commodity mobile devices through sound signalsPersonal and Ubiquitous Computing10.1007/s00779-019-01337-724:5(643-654)Online publication date: 13-Nov-2019
    • (2018)Understanding Face and Eye Visibility in Front-Facing Cameras of Smartphones used in the WildProceedings of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3173574.3173854(1-12)Online publication date: 21-Apr-2018
    • (2017)Towards grip sensing for commodity smartphones through acoustic signatureProceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers10.1145/3123024.3123090(105-108)Online publication date: 11-Sep-2017
    • (2017)Finding Common GroundProceedings of the 2017 CHI Conference on Human Factors in Computing Systems10.1145/3025453.3025808(3293-3315)Online publication date: 2-May-2017
    • Show More Cited By

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