Summary
This paper first describes some features of a gesture based drawing program which uses GRANDMA (Gesture Recognizers Automated in a Novel Direct Manipulation) developed by Dean Rubine. The system uses training examples of various gestures to recognizer and classify the input from the user. Several training examples of the "delete" gesture are shown to illustrate the variety possible in a single gesture. Next the features used for gesture recognition are described. These features are used in combination with a linear classifier to determine which class a gesture belongs to. A few example gesture sets are also given along with their respective recognition rates to demonstrate the high accuracy provided by GRANDMA.
Discussion
In 1991, Rubine's GRANDMA system provided a solid framework for gesture recognition based on example gestures. This method proved relatively simple compared to implementing the hand-coded recognizers available at the time. Having a system that can be trained using example gestures allows for easier custom implementations in various types of programs. The feature set chosen by Rubine combined with the linear classifier is sufficient to repeatedly distinguish most common gestures as well as numbers and letters as shown in Figure 9 of the paper.
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