Summary
In this paper, the introduces a series of smaller programs which when intertwined form the basis of a graphical input recognition system named HUNCH. Some basic issues in sketch recognition are discussed including how to find lines and corners from raw data and how to methods for dealing with latching and over-tracing. Underlying problems of the bottom-up approach for recognition are also discussed and brief exploration is given into how a top-to-bottom approach might function.
Discussion
In a modern sketch recognition system, many of the smaller programs implemented here may simply be seen as function of a complete recognition program. However, since at the time, computer resources were limited, the process of breaking up the recognition process into smaller tasks provides great insight into the basic steps to be taken for recognition. It is also interesting that in order to locate corners, the author utilizes speed and "bentness". "Bentness" later proved to be a very effective method of locating corners as seen in the Short-Straw method discussed in class. Although it may not have been as effective at the time of this writing since they most likely lacked the computer resources to re-sample a sketch.
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