We are trying to have an online handwritten text recognizer for the Android platform. The inbuilt Gesture Recognition in android uses (from what I gather from the code) a K-NN checking of points, most probably the control points of a smoothed Bezier curve.
Instead of that we’ll get some standard feature data from the points generated by the user on the touchscreen and then train an SVM for about 50 character classes (initially) to check how well our feature selection is working.
So considering that this SVM will have to run on a mobile phone which may not be state of the art in terms of processing power, which library should be used? Also to be considered is which library will be most easily integrated into development on the Android SDK using Eclipse IDE?
I have LibSVM in mind, but anyone with experience of using such on mobile platform should be able to give an educated guess of what to go for.
Thanks in advance.
I gather that what you need to do on the Android device is only evaluating the SVM on new data and not training. In that case, you really don’t need any library. You just need to output the model (the weights) from LIBSVM or whatever library/method you plan to use, into your source code (whatever it is) and evaluate it on new data as your Android application requires.