Hello.
My name is Fedor Morozov, I'm a third year CS student at Moscow State University specializing in computer vision.
Since touchscreen devices are highly popular nowadays, there are lots of cases when it's easier to handwrite a formula then to enter it using a keyboard.
State-of-the arts computer vision approaches achieve good results in formula recognition, so it is possible to implement such a feature for SymPy Gamma.
Along with NLP parsing this would provide a very powerful user input capabilities.
There are already some similar 3rd-party applications for Wolfram Alpha, you can see an example
here.
A more challenging task would be formula recognition from photos, but that's not necessary right now, I guess.
So the proposed project is to implement formula recognition capabilities for SymPy Gamma, it would also be great to make some interface for touchscreen input (web/mobile app?).
I've recently read a few articles on the topic, if you believe that the project if useful, I'll come up with a full-fledged proposal and algorithms review.
The easiest (conceptually) approach would be to select some of the recent articles and code up the algorithm.
Than some improvements can be made, for example it would be cool to use SymPy resources for formula correctness checking.
As stated above, I specialize in computer vision, so I'm familiar with basic algorithms in the area.
Now I'm researching feature descriptors, so I have some experience with shape recognition (for example, shape context), a year ago I worked on a car plate recognition task.
Also last year I participated in GSoC with computational photography project for opencv library.
Thanks for your attention, hope to hear some comments soon.