CHI '04 Extended Abstracts on Human Factors in Computing Systems
International Journal of Human-Computer Studies - Special issue: Fitts law 50 years later: Applications and contributions from human-computer interaction
Toss-It: Intuitive Information Transfer Techniques for Mobile Devices Using Toss and Swing Actions
IEICE - Transactions on Information and Systems
Fitts' law as a research and design tool in human-computer interaction
Human-Computer Interaction
Motion-pointing: target selection using elliptical motions
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
User-defined gestures for surface computing
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Usable gestures for mobile interfaces: evaluating social acceptability
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
User-defined gestures for connecting mobile phones, public displays, and tabletops
Proceedings of the 12th international conference on Human computer interaction with mobile devices and services
A novel taxonomy for gestural interaction techniques based on accelerometers
Proceedings of the 16th international conference on Intelligent user interfaces
Information capacity of full-body movements
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Tweetris: a study of whole-body interaction during a public art event
Proceedings of the 9th ACM Conference on Creativity & Cognition
Understanding the consistency of users' pen and finger stroke gesture articulation
Proceedings of Graphics Interface 2013
CUBOD: a customized body gesture design tool for end users
BCS-HCI '13 Proceedings of the 27th International BCS Human Computer Interaction Conference
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This paper presents a systematic and general technique for establishing a set of motions suitable for use with sensor systems, by drawing performable and measurable motions directly from users. It uses reinforcement which rewards originality to induce users to explore the space of motions they can perform. A decomposition of movements into motion primitives is constructed, among which a meaningful originality metric can be defined. Because the originality measure is defined in terms of the sensed input, the resulting space contains only movements which can both be performed and sensed. We show how this can be used to evaluate the relative performance of different joint user-sensor systems, providing objective analyses of gesture lexicons with regard to the technical limitations of sensors and humans. In particular, we show how the space of motions varies across the arm for a body-mounted inertial sensor.