A dynamic gesture recognition system for the Korean sign language (KSL)
Kim et al use a combination of Cybergloves and 3d position sensors to capture Korean sign language gestures using template matching and neural neworks. The overall gesture is match to templates. The x and y axis are divided into 8 regions and the motion of the gesture is tracked as positive or negative changes in region. Each gesture is matched to a set of template region changes to determine. Posture recognition is performed using Fuzzy Min Max Networks. Each class is determined by a max and min point defining a hyperbox and a membership function. After matching a sequence of positions to a template, the posture is used to determine which sign is represented.
Discussion
Gesture templates exist only in 2D; however it should be fairly easy to extend. Some of the templates seem to not match the motions from Figure 2. The templates also limit place a limit on the size of gestures performed.
Reference
J. S. Kim,W. Jang, and Z. Bien, "A dynamic gesture recognition system for the Korean sign language (KSL)," IEEE Trans. Syst., Man, Cybern. B, vol. 26, pp. 354–359, Apr. 1996.
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