Comment:
Chris
Summary:
The paper uses bayesian conditional random fields to recognize sketched diagrams. Instead of recognize each element of digrams individually, they jointly analyzes all drawing elements in order to incorporate contextual cues. The classification uses the spatial and temporal information, and they have made a great assumption that classifying one object has impact one another object. The idea is very important when we utilizing the context informaiton into sketch recogniton. The result shows that their method can avoid overfitting problem and much better than maximum likehood and Maximum a posterior trained CRFs. The majority of this paper focused on mathematical detail of implementaiton.
Disccusion:
What a fantastic paper! The paper shows my initial idea about sketch recognition. I am always beliving that without context information of sketch, the recogniton is not feasible in most of cases, at least, does not obtain high accuracy. In order to maximize recognition accuracy, we must use the context information, also for the shape vs text task. They use baysian theory to incorpate this context information into their recogniton result. This is very very nice paper, and worth carefully reading it.
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