Reading #8. A Lightweight Multistroke Recognizer for User Interface Prototypes (Anothony)

COMMENTS:

Paco

SUMMARY:

This paper discusses $N, an extension of the $1 recognizer created by Wobbrok.  The $N recognizer has the following enhancements:

-          recognizes gestures comprised of multiple stroke

-          generalizes from one multistroke to all multistrokes

-          recognizes one-dimensional gestures

-          provides bounded rotation variance

The authors give an overview of the $1 recognizer and then explain the enhancements of the $N recognizer and how they are implemented.  The $N recognizer was 96.6% and 96.7% accurate on algebra symbols and unistroke collection respectively.

DISCUSSION:

The $N recognizer is an impressive enhancement to $1, and 240 lines of code, it is still fairly lightweight.  I like how the authors presented both the strengths and the weaknesses of the recognizer in detail.  I believe that the segmentation issue which was not addressed by the recognizer could be handled by input from the user and would not present a huge hindrance to the effectiveness of the recognizer.

My only concern was the training method; 15 training examples were used for the algebra symbols, however only 9 example were used for the unistroke gestures.  Given that the recognition accuracy rate only differed by .1% the number of examples did not have a significant affect, but I wonder why the training examples were not kept consistent in order to eliminate the number of examples as a factor in the performance difference.  Also, I felt that the authors should have tried to match as many elements of the $1 testing as possible (i.e. testing with adults instead of students).