Aman Parnami
Apurva Gupta
Gabriel Reyes
ABSTRACT
We present Mogeste, a smartphone-based tool, to enable rapid, iterative, in-situ motion gesture design by interaction designers. It supports development of in-air gestural interaction with existing inertial sensors on commodity wearable and mobile devices. Mogeste facilitates creation of prototypical gesture recognizers by designers through an programming by demonstration approach. Furthermore, it makes testing and updating these preliminary designs easy. By eliminating the need for coding and pattern recognition expertise, Mogeste frees the designer to explore several gesture designs in a matter of minutes. Finally, our mobile solution builds upon previous work in desktop-based authoring tools for sensor-based interactions and, in doing so, enables creative exploration by designers in naturalistic settings.
- Shahriyar Amini and Yang Li. 2013. CrowdLearner: rapidly creating mobile recognizers using crowdsourcing. In Proc. CHI. 163--172. Google Scholar
Digital Library
- Daniel Ashbrook, Patrick Baudisch, and Sean White. 2011. Nenya: Subtle and Eyes-free Mobile Input with a Magnetically-tracked Finger Ring. In Proc. CHI. 2043--2046. Google ScholarDigital Library
- Daniel Ashbrook and Thad Starner. 2010. MAGIC: A Motion Gesture Design Tool. In Proc. CHI. 2159--2168. Google ScholarDigital Library
- Daniel Lee Ashbrook. 2010. Enabling mobile microinteractions. Ph.D. Dissertation. Georgia Institute of Technology, Atlanta, GA.Google ScholarDigital Library
- Allen Cypher and Daniel Conrad Halbert. 1993. Watch what I do: programming by demonstration. MIT press. Google ScholarDigital Library
- Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, and Ian H. Witten. 2009. The WEKA data mining software: an update. SIGKDD (2009), 10--18. Google ScholarDigital Library
- Nils Y. Hammerla, Reuben Kirkham, Peter Andras, and Thomas Ploetz. 2013. On preserving statistical characteristics of accelerometry data using their empirical cumulative distribution. In Proc. ISWC. 65. Google ScholarDigital Library
- Bjoern Hartmann, Leith Abdulla, Manas Mittal, and Scott R. Klemmer. 2007. Authoring Sensor-based Interactions by Demonstration with Direct Manipulation and Pattern Recognition. In Proc. CHI. 145--154. Google ScholarDigital Library
- Ju-Whan Kim, Han-Jong Kim, and Tek-Jin Nam. 2016. M.Gesture: An Acceleration-Based Gesture Authoring System on Multiple Handheld and Wearable Devices. In Proc. CHI. 2307--2318. Google ScholarDigital Library
- Matei Negulescu, Jaime Ruiz, Yang Li, and Edward Lank. 2012. Tap, Swipe, or Move: Attentional Demands for Distracted Smartphone Input. In Proc. AVI. 173--180. Google ScholarDigital Library
- Dean Rubine. 1991. Specifying gestures by example. Vol. 25. Google ScholarDigital Library
Index Terms
- Mogeste: mobile tool for in-situ motion gesture design
Recommendations
Mogeste: A Mobile Tool for In-Situ Motion Gesture Design
IndiaHCI '16: Proceedings of the 8th Indian Conference on Human-Computer InteractionMotion gestures can be expressive, fast to access and perform, and facilitated by ubiquitous inertial sensors. However, implementing a gesture recognizer requires substantial programming and pattern recognition expertise. Although several graphical ...
Smartwatch-based Early Gesture Detection 8 Trajectory Tracking for Interactive Gesture-Driven Applications
The paper explores the possibility of using wrist-worn devices (specifically, a smartwatch) to accurately track the hand movement and gestures for a new class of immersive, interactive gesture-driven applications. These interactive applications need two ...
Leap gestures for TV: insights from an elicitation study
TVX '14: Proceedings of the ACM International Conference on Interactive Experiences for TV and Online VideoWe present insights from a gesture elicitation study in the context of interacting with TV, during which 18 participants contributed and rated the execution difficulty and recall likeliness of free-hand gestures for 21 distinct TV tasks. Our study ...
Comments