002 - Rubine's "Specifying Gestures by Example"

Summary:

This paper covers the GRANDMA system, or Gesture Recognizers Automated
in a Novel Direct Manipulation Architecture, which seems to be a very simple gesture-recognizing tool to add any number of gestures to a program, as used with the GDP drawing program. It starts with an example of the system doing some of it's main gestures in a series, including copying, moving, drawing a line, and deletion. Explaining the hierarchy of the GDP, it shows how the gestures are put in and handled. Using a number of examples, it states that almost any gesture can be expressed in this way regardless of size and style. It contrasts this with the multi-stroke techniques that were used in the day, explaining how this improves both techniques and adds flexibility. It then delves into the features used for the underlying algorithm, and how each is calculated and used. It explains the training process and why it works, as well as the rejection and evaluation processes. It further explains some extensions that could be used to improve the overall recognition. This paper is FULL of equations that will be very useful for any recognition system.

Discussion:

I just can't help think that there's some easier way to do this. Obviously much research was done in this area and this is a VERY nice list of features that has been proven to work, but I somehow feel like this is overkill. Maybe there aren't easier ways with less features out there, but I'd like to think there are.

I think this paper is a really great source of information. The list of equations is extensive and pretty laid out bare. I liked the idea of Eager Recognition more than waiting for the system to recognize it, though Rubine doesn't cover it very in-depth.

I commend Rubine for all this research, but I also personally think there's a threshold that we really should stop caring about. Everyone's style is different, so I'm not sure there will ever be a 100% recognition mark for the world's population. Heck, I don't think there'll ever be a 100% recognition mark for our class's population. It's nice to know all this data, but I think, as Rubine said, as long as programs have decent undo functions we shouldn't overwork ourselves to get that 1 extra percent.