Reading #10. Graphical Input Through Machine Recognition of Sketches (Herot)

Comments
Chris Aikens
Summary

The paper is motivated by the desire to involve computers into the design process. It involves the user to make decision. The contribution of this paper is to involve the user in the system and make the system interactive. To involve the user, the system adopts some extra functions and context. These functions aim to capture users' intention, and context makes the system closed to the way of human thinking.
The paper firstly gives the introduction of their previous work-HUNCH system, introducing the low-level inference in it, like latching, overtracing and so on. The key assumption in the HUNCH is that speed is the intention of the user, however, which always causes errors in the system.

The author develops the system by introducing the high-level of inference-context and improving the low-level inference.The structure of context in HUNCH is context-free, as the figure below. The structure of context in the new system is context-based, as the figure below.

context-free

context based

The main program will see a tablet which produces not only X, Y and Z but also speed, bentness, corners, and curves. They will be used in inference-making. The scale that the user worked will be determined by other cluse, such as busyness. The main program will run in the background, without interrupting users. The low-level inference starts when the user begins to draw, while the high-level inference starts when the user stops.

Discussion

A very old paper, but some excellent ideas. Context, in my opinion, is very important in high-level recognizing.  I guess, it may be the first time to introduce context in the sketch recognition. The core of it is to involve the user to make decision, which actually is now very often used in our recognition. The feedback, or backtrace seems important in the recognition, which is better than the traditional method, like bottom-up.

But there is very few details in the paper about how the context worked. Is there some methods to obtain the result from the context, like Markov?  Also, I cannot really understand what the paper want to express, but I can find some excellent ideas in it.