The AGreement Analysis Toolkit (AGATe) is an application and associated reusable library (DLL)
named AgreementRates.dll that supports the
user-defined gesture elicitation methodology
by calculating agreement rate statistics on data collected using this methodology. The methodology
allows users to propose gestures to accomplish specified tasks in human-computer interaction,
and final gesture sets are designed to
maximize the guessability
of the adopted gestures.
R Code for Agreement Rate Statistics
Download this "R-agreement.zip" archive for R code that implements simulation experiments to estimate the Type I error
and power for a variety of statistical tests, including Vrd(Vatavu & Wobbrock, 2015),
Vb(Vatavu and Wobbrock, 2016),
the percentile bootstrap, and others, for comparing agreement rates in within- and between-subjects end-user elicitation studies.
Our code uses Rand Wilcox's "Rallfun" R library for robust statistics. The main
entry point of our code is the "main.R" file that runs all the simulation experiments.
AGATe 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.