Paper
Alvarado, Christine, and Randall Davis. "SketchREAD: a multi-domain sketch recognition engine." Proceedings of the 17th annual ACM symposium on User interface software and technology. ACM, 2004.
Publication Link: http://dl.acm.org/citation.cfm?id=1029637
Publication Link: http://dl.acm.org/citation.cfm?id=1029637
Summary
The paper describes the design and implementation of a sketch recognition system, which can be used in multiple domains to recognize hand-drawn diagramatic sketches. SketchREAD uses a context guided sketch recognition approach and utilizes Bayesian networks for interpretation and verification of recognized strokes.
With their approach, the system is able to detect and recover from low level recognition errors.
They evaluated the performance of sketchREAD in comparison with basic bottom-up recognizer on two differing domains: recognition of family tree diagrams, and recognition of circuit diagrams. They also evaluated the runtime performance of their system, noting frequent wostcase running time occurrence on strokes drawn within close proximity.
Discussion
With their approach, the system is able to detect and recover from low level recognition errors.
They evaluated the performance of sketchREAD in comparison with basic bottom-up recognizer on two differing domains: recognition of family tree diagrams, and recognition of circuit diagrams. They also evaluated the runtime performance of their system, noting frequent wostcase running time occurrence on strokes drawn within close proximity.
Discussion
Pros
A novel use of HMMs that is reminiscent of uses in speech recognition and NLP.
Cons.
The description of the BayesNET algorithm wasn't very clear and could have been enhanced with a more simple diagram. Some of the inferences from their figures was also very unclear.
The description of the BayesNET algorithm wasn't very clear and could have been enhanced with a more simple diagram. Some of the inferences from their figures was also very unclear.
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