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.
Video
Our Gesture Software Projects
$Q: Super-quick multistroke recognizer - optimized for low-power mobiles and wearables
$P+: Point-cloud multistroke recognizer - optimized for people with low vision
$P: Point-cloud multistroke recognizer - for recognizing multistroke gestures as point-clouds
$N: Multistroke recognizer - for recognizing simple multistroke gestures
$1: Unistroke recognizer - for recognizing unistroke gestures
AGATe: AGreement Analysis Toolkit - for calculating agreement in gesture-elicitation studies
GHoST: Gesture HeatmapS Toolkit - for visualizing variation in gesture articulation
GREAT: Gesture RElative Accuracy Toolkit - for measuring variation in gesture articulation
GECKo: GEsture Clustering toolKit - for clustering gestures and calculating agreement
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.
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.