$1 Unistroke Recognizer
depts.washington.edu
depts.washington.edu
Their implementation is quite clean, it really is a nice clean algorithm. It takes reading it to understand the type of shapes (templates) that work best and also as a user how best to draw them. I added a demo that shows you as you draw what it's internal state is and best guess so far: http://francoislaberge.com/outlines/demo/index.html
It seems like it might be tricky to train it on what not to recognise. Or maybe you just need a lot of template gestures.
Hmmm, and yeah you could add templates that are variants of an intended output. To improve the chance of matching important gestures
I built a pretty cool tweak for iOS 5 that integrated it into the operating system:
https://www.youtube.com/watch?v=35SX6A9fE0g
I haven't thought about it in a long time, but I still think that these gestures could be a great shortcut interface for a multi-touch OS, especially with pressure sensitivity. A deep press could activate the gesture recognizer.
I think it's a neat toy, but frankly I don't understand what attracts GUI designers to gestures. They seem lot more complicated than just buttons (even if you would have to push an extra button to get the menu), they are not obvious and you have to learn them to do correctly. Am I missing something?
They could 'fix' this by adding reverse forms of each of the strokes. I wonder why they haven't? Does doing so drastically reduce the detection accuracy?
In contrast, human-to-human communication consider much (most?) of the space of possible speech acts to be gibberish.
In other words, the software never gives up on trying to classify a user-input sequence no matter how wacky it is.
For example, } drawn from bottom up is "recognized" as {.
Once you get that, it's fairly accurate.