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Gesture HeatmapS Toolkit (GHoST)

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

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Current Version: 0.1 2014-04-29

Windows executable: EXE
GHoST source code: C#
DLL source code: C#
Paper: PDF
Poster: PDF

Microsoft .NET 4.5 Framework required. Download it here.
This software is distributed under the New BSD License agreement.

About

The Gesture HeatmapS Toolkit (GHoST) is an application and associated reusable library (DLL) named RelativeAccuracyMeasures.dll that allows researchers, gesture designers, or usability specialists to examine the articulation properties of stroke gestures via gesture heatmaps, which are color map visualizations of how gestures vary in time and space as they are articulated. Gesture heatmaps show how various properties of stroke gestures vary locally along their path. Properties include shape error, turning angle, or speed. Colors communicate relative values. For example, "warm" orange and red colors usually indicate more magnitude in the data, while "cold" colors, such as green and blue, are used to encode data values with smaller magnitudes. GHoST also provides chromatic confusion matrices that employ gesture heatmaps to reveal gesture classification performance.

Video

Our Gesture Software Projects

Our Gesture Publications

Vatavu, R.-D. and Wobbrock, J.O. (2016). Between-subjects elicitation studies: Formalization and tool support. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI '16). San Jose, California (May 7-12, 2016). New York: ACM Press, pp. 3390-3402.

Vatavu, R.-D. and Wobbrock, J.O. (2015). Formalizing agreement analysis for elicitation studies: New measures, significance test, and toolkit. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI '15). Seoul, Korea (April 18-23, 2015). New York: ACM Press, pp. 1325-1334.

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 © 2014-2016 Jacob O. Wobbrock. All rights reserved.
Last updated December 23, 2016.