Tilting operations for small screen interfaces
Proceedings of the 9th annual ACM symposium on User interface software and technology
Squeeze me, hold me, tilt me! An exploration of manipulative user interfaces
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Sensing techniques for mobile interaction
UIST '00 Proceedings of the 13th annual ACM symposium on User interface software and technology
Rock 'n' Scroll Is Here to Stay
IEEE Computer Graphics and Applications
Design and analysis of delimiters for selection-action pen gesture phrases in scriboli
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Experimental analysis of mode switching techniques in pen-based user interfaces
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes
Proceedings of the 20th annual ACM symposium on User interface software and technology
Usable gestures for mobile interfaces: evaluating social acceptability
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
User-defined motion gestures for mobile interaction
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
JerkTilts: using accelerometers for eight-choice selection on mobile devices
ICMI '11 Proceedings of the 13th international conference on multimodal interfaces
Gesture-based interaction: a new dimension for mobile user interfaces
Proceedings of the International Working Conference on Advanced Visual Interfaces
Tap, swipe, or move: attentional demands for distracted smartphone input
Proceedings of the International Working Conference on Advanced Visual Interfaces
Small gestures go a long way: how many bits per gesture do recognizers actually need?
Proceedings of the Designing Interactive Systems Conference
A recognition safety net: bi-level threshold recognition for mobile motion gestures
MobileHCI '12 Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services
Cell phone puppets: turning mobile phones into performing objects
ICEC'12 Proceedings of the 11th international conference on Entertainment Computing
The impact of motion dimensionality and bit cardinality on the design of 3D gesture recognizers
International Journal of Human-Computer Studies
Proceedings of the 2013 international conference on Intelligent user interfaces
Bezel-Tap gestures: quick activation of commands from sleep mode on tablets
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
CrowdLearner: rapidly creating mobile recognizers using crowdsourcing
Proceedings of the 26th annual ACM symposium on User interface software and technology
LensGesture: augmenting mobile interactions with back-of-device finger gestures
Proceedings of the 15th ACM on International conference on multimodal interaction
Motion and context sensing techniques for pen computing
Proceedings of Graphics Interface 2013
Extending the vocabulary of touch events with ThumbRock
Proceedings of Graphics Interface 2013
Hacking the Gestures of Past for Future Interactions
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
Favoured attributes of in-air gestures in the home environment
Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration
Teaching motion gestures via recognizer feedback
Proceedings of the 19th international conference on Intelligent User Interfaces
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To make motion gestures more widely adopted on mobile devices it is important that devices be able to distinguish between motion intended for mobile interaction and every-day motion. In this paper, we present DoubleFlip, a unique motion gesture designed as an input delimiter for mobile motion-based interaction. The DoubleFlip gesture is distinct from regular motion of a mobile device. Based on a collection of 2,100 hours of motion data captured from 99 users, we found that our DoubleFlip recognizer is extremely resistant to false positive conditions, while still achieving a high recognition rate. Since DoubleFlip is easy to perform and unlikely to be accidentally invoked, it provides an always-active input event for mobile interaction.