21 - SketchREAD

Summary:

Alvarado's SketchREAD is a system based on Bayesian networks to cut down on the time-consuming task of checking every line with every template match. The system uses both a top-down method and a bottom-up approach. The top-down comes from unfinished shapes, and looks for the missing pieces of possible template matches. It will do this continuously if necessary. Bottom-up is similar to LADDER's approach, where each drawing is recognized as a primitive and the drawing builds upon itself. The system will also "prune" interpretations from the top-down approach, finally selecting the best fit after removing all the unlikely ones. Results show that SketchREAD improves upon baseline numbers, very highly in trees and significantly in circuit diagrams as well.

Discussion:

I wish I could test this system out. This system seems like a very nice alternative to LADDER and definitely in the running. I believe the different methods used within SketchREAD should definitely be looked at more closely, as using both top-down and bottom-up recognition techniques seems to be a great asset. I think integrating these techniques into existing systems would almost always increase recognition, but without knowing all the domains that exist, it's not certain. Still, I'd like to see more domains tested with these innovative ideas.