007 - Domain-Independent System by Yu

Summary:

This paper deals with Yu et. al basically adding on to Sezgin's model. They begin with a list of attributes that they believe are essential in any sketch recognition software and explains why their system qualifies as such. The next section explains their concept of "feature area", which is somewhat similar to error except it deals with various primitives. They then move on to explain how their system does vertex detection, line and curve approximation, and self-intersections. The vertexes are using basic primitives instead of speed data to approximate points. The line and curve approximations are fairly elementary, with basic examples given by the direction graph of various shapes and how they correspond. The self-intersection is handled by checking to see if it is possible and cutting it if is not. The paper then explains some of the cleanup and how the primitives work with the sketches to test for errors. It then concludes with a user study that ended with decent success on most simple shapes and met with user satisfaction.

Discussion:

To be honest, I loved this paper. It really brings everything down to earth and has simple solutions. Granted, this system has a LOT of errors when you start dealing with more distinct shapes, but for simple tools like AutoCad (which is mentioned at the end of the paper) this system would cut user time in half, which is nothing to scoff at. I think this system is a step in the right direction, even though it seems to just further the work of Sezgin. I believe approximation is a much more beneficial direction than that of perfect recognition.