GEsture Clustering toolKit (GECKo)

Lisa Anthony, University of Maryland—Baltimore County
Radu-Daniel Vatavu, University Stefan cel Mare of Suceava
Jacob O. Wobbrock, University of Washington [contact]

Currently at the University of Florida

Download

Current Version: 1.0.4-2012.08

Windows executable: EXE
GECKo source code: C#
Multistroke gesture logs: XML
Paper: PDF
Video: AVI

Microsoft .NET 4.0 Framework required. Download it here.
This software is distributed under the New BSD License agreement.

About

The GEsture Clustering toolKit (GECKo) makes it easy to study the manner in which users articulate stroke gestures. GECKo clusters and visualizes stroke gestures according to stroke number, order, and direction, enabling interactive gesture playback and auditing of the clustering results. GECKo also reports within- and between-subject agreement rates after clustering. GECKo will be useful to gesture researchers and developers who wish to better understand how users make gestures, especially when complex multistroke gestures are involved. The gestures produced as part of the research on the $N multistroke recognizer, known as the Mixed Multistroke Gesture (MMG) dataset, are offered for exploration with GECKo.

Our Related Software Projects

Our Related Publications

Vatavu, R.-D., Anthony, L. and Wobbrock, J.O. (2014). Gesture heatmaps: Understanding gesture performance with colorful visualizations. Proceedings of the ACM International Conference on Multimodal Interfaces (ICMI '14). Istanbul, Turkey (November 12-16, 2014). New York: ACM Press, pp. 172-179.

Vatavu, R.-D., Anthony, L. and Wobbrock, J.O. (2013). Relative accuracy measures for stroke gestures. Proceedings of the ACM International Conference on Multimodal Interfaces (ICMI '13). Sydney, Australia (December 9-13, 2013). New York: ACM Press, pp. 279-286.

Anthony, L., Vatavu, R.-D. and Wobbrock, J.O. (2013). Understanding the consistency of users' pen and finger stroke gesture articulation. Proceedings of Graphics Interface (GI '13). Regina, Saskatchewan (May 29-31, 2013). Toronto, Ontario: Canadian Information Processing Society, pp. 87-94.

Vatavu, R.-D., Anthony, L. and Wobbrock, J.O. (2012). Gestures as point clouds: A $P recognizer for user interface prototypes. Proceedings of the ACM International Conference on Multimodal Interfaces (ICMI '12). Santa Monica, California (October 22-26, 2012). New York: ACM Press, pp. 273-280.

Anthony, L. and Wobbrock, J.O. (2012). $N-Protractor: A fast and accurate multistroke recognizer. Proceedings of Graphics Interface (GI '12). Toronto, Ontario (May 28-30, 2012). Toronto, Ontario: Canadian Information Processing Society, pp. 117-120.

Anthony, L. and Wobbrock, J.O. (2010). A lightweight multistroke recognizer for user interface prototypes. Proceedings of Graphics Interface (GI '10). Ottawa, Ontario (May 31-June 2, 2010). Toronto, Ontario: Canadian Information Processing Society, pp. 245-252.

Wobbrock, J.O., Wilson, A.D. and Li, Y. (2007). Gestures without libraries, toolkits or training: A $1 recognizer for user interface prototypes. Proceedings of the ACM Symposium on User Interface Software and Technology (UIST '07). Newport, Rhode Island (October 7-10, 2007). New York: ACM Press, pp. 159-168.


Copyright © 2013-2014 Jacob O. Wobbrock