20 - 1$ Recognizer

Summary:

Wobbrock et al explain their new recognizer that can be written with little mathematical background in this system. It's given in four easy to follow steps - resampling, rotation, scaling, and classification. It begins by taking N samples from the gesture, defined by the system designer, then rotates it to be horizontal from the start point to the middle of the gesture (N/2 point). Then the gesture is scaled to fit in a specified bounding box and translated to be at the origin. The gesture is then error-checked by the system to match to the list of existing shapes. Results are very high (around 98%) with simple shapes and a decent amount of existing templates.

Discussion:

While this recognizer seems to have no significance in furthering the field, I believe it is necessary to the advancement into the next evolution of sketch recognition. The real benefit of this system is not in how much it advances the field, but more in how it draws new people into the field. This system is meant as a "first step" into sketch recognition, which was, before now, Rubine's feature system. As a beginner in the field myself, I see this paper as a much prettier and "fun" approach of entering sketch recognition, as Rubine's method is much more intimidating than this sytem. I believe that this system will be useful in drawing fresh ideas from less mathematically inclined designers.