$-Family of Gesture Recognizers

Along with my colleagues Jacob Wobbrock at UW and Radu-Daniel Vatavu at University Stefan Cel Mare of Suceava, I have been working on developing, evaluating and extending a suite of simple, fast, accurate pen and finger gesture recognizers, which we call the “$-family”.

The $-family began as an extension to Wobbrock et al’s $1 unistroke gesture recognition algorithm. The goal of $N, like $1 before it, is to implement a simple, fast, reasonably accurate recognizer that can be easily incorporated into rapid prototyping processes, to give application designers the power of trying out different input methods without having to spend a lot of effort getting the recognition up and running. Try out an online demo of $N in JavaScript, and check out the detailed pseudocode listing. $N has some limitations, of course, but in our preliminary experiments, it has performed comparably to well-known recognizers, with much lower start-up costs.

We recently introduced $P, the newest and most robust member of the $-family so far. $P can recognize gestures made with any number of strokes in any order or direction with low storage cost, whereas $N had high storage costs since it internally represented all the same variations that $P’s matching algorithm can handle seamlessly. Try out an online demo of $P in JavaScript, and check out its detailed pseudocode listing.

For help in choosing the best member of the $-family for your needs, check out the “cheat sheet” which we include in the $P paper. Also, we provide more detailed information, and C# reference implementations, on our full project websites for both $N and $P!


  1. Vatavu, R., Anthony, L., and Wobbrock, J.O. 2012. Gestures as Point Clouds: A $P Recognizer for User Interface Prototypes. Proceedings of ACM International Conference on Multimodal Interaction (ICMI’2012), Santa Monica, CA, p.273-280. [pdf] best paper award!
  2. Anthony, L. and Wobbrock, J.O. 2012. $N-Protractor: A Fast and Accurate Multistroke Recognizer. Proceedings of Graphics Interface (GI’2012), Toronto, Canada, p.117-120. [pdf]
  3. Anthony, L. and Wobbrock, J.O. 2010. A Lightweight Multistroke Recognizer for User Interface Prototypes. Proceedings of Graphics Interface (GI’2010), Ottawa, Canada, 02 Jun 2010, p.245-252. [pdf]

last revised 11/08/2012

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