Graphical Input through Machine recogniton of sketches

-Christopher F. Herot

COMMENTS

1. Comment on Ben's blog

SUMMARY

The paper talks about a family of programs employed in sketch recognition. The author mentions that all the previous attempts have have not used human intervention to assist recognition. It is further claimed that even the basic recognition requires context information, which in the later part of paper is shown to be best gathered by asking the user.
The HUNCH system was conceived around a program called STRAIT. It found corners in a figure by finding minima in the speed curve. When the curvature of the corner was to gradual, it caused subsequent invocation of the CURVIT program. But experiments show that it had been modeled for a specific set of users only and had inaccurate results with others. Next, other techniques employed to improve recognition are discussed. Latching is a technique in which any end-points within a threshold distance are joined. Overtracing is a technique to turn several closely lying lines into one. However both these techniques sometimes cause unwanted actions (like joining of corners, intentionally drawn close).
Thus any bottom-up approach is hindered by lack of contextual information. getting context information without human intervention is akin to problem in AI which are hard to solve.
The author then describes a system built around human input for getting context. One important difference between this system and the previous ones, is the existence of a graphical manipulator/editor which user can use to make correction to the predicted output of the system, implicitly providing context information.
In the end several ways to improve latching technique are discussed.

DISCUSSION
What we learned from this paper provides a different perspective on sketch recognition. What we aim at is sketch-recognition without explicit user assistance. On the other hand the author claims that user-assistance might be pivotal in recognition. Whether this is a fault with this claim, or is it the right way to go can be determined by conducting user studies and getting feedback as to whether they find it natural and easy to assist the recognition programs. If users indeed find this natural, then it could considerably reduce the complexity of sketch recognition research.