Feb 01, 2015 Trustworthy sites like major geeks and file hippo don't have the gecko toolkit. Special thanks to malware bytes, avg, adwcleaner for the cleanup. Thanks apple for putting us through this very unnecessary problem. Thanks windows for a whole different set of problems. Download the Gecko iPhone toolkit, you can find it for free. Restore those files you backed up on iCloud or iTunes to your iPhone or Mac/PC. Just Download Gecko iPhone Toolkit and Install it and follow the steps. Of your iOS device using Gecko iOS Toolkit on Windows or Mac.
GEsture Clustering toolKit (GECKo)
Jan 20, 2020 If you need Gecko to run an app in Wine, follow the instructions above. Wine Gecko source is hosted in Git on Sourceforge. Wine Gecko is maintained by Jacek Caban. If you need help, feel free to contact him. It is encouraged to use mingw-w64 for cross-compiling. A fairly recent version of mingw-w64 should be enough. Jan 31, 2019 However, before you jump straight to downloading the Gecko toolkit, you must first see whether it is compatible with your device. The compatible iOS versions and device models for the Gecko iPhone toolkit are: iPhone 4, iPhone 3GS, iPad 1, iPod Touch 3G, iPod touch 4G. Compatible with iOS 4.0 to 6.x.x. The Gecko Toolkit functions with a variety of iOS versions but is dependent on the correct.NET frame work, Java and iTunes version. If you are running anything above 5.1.1 you may need to experiment with different combinations of all the above.
Lisa Anthony, University of Maryland—Baltimore County† Radu-Daniel Vatavu, University Stefan cel Mare of Suceava Jacob O. Wobbrock, University of Washington ?subject=From the GECKo page'>[contact]
†Currently at the University of Florida
Download
Current Version: 1.0.5-2016.04
Windows executable: EXE GECKo source code: C# Multistroke gesture logs: XML Paper: PDF
Microsoft .NET 4.0 Framework required. Download it here. This software is distributed under the New BSD License agreement.
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
Our Gesture Publications
Gecko Toolkit For Mac Download
Vatavu, R.-D., Anthony, L. and Wobbrock, J.O. (2018). $Q: A super-quick, articulation-invariant stroke-gesture recognizer for low-resource devices. Proceedings of the ACM Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI '18). Barcelona, Spain (September 3-6, 2018). New York: ACM Press. Article No. 23.
Vatavu, R.-D. (2017). Improving gesture recognition accuracy on touch screens for users with low vision. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI '17). Denver, Colorado (May 6-11, 2017). New York: ACM Press, pp. 4667-4679.
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.