New Generation Computing, 18(2000)89-101
Ohmsha, Ltd. and Springer-Verlag
Received 31 August 1999
Revised manuscript received 14 October 1999
We have developed a real-time gesture recognition system whose models can be taught by only one instruction. Therefore the system can adapt to new gesture performer quickly but it can not raise the recognition rates even if we teach gestures many times. That is because the system could not utilize all the teaching data. In order to cope with the problem, averages of teaching data are calculated. First, the best frame correspondence of the teaching data and the model is obtained by Continuous DP. Next the averages and variations are calculated for each frame of the model. We show the effectiveness of our method in the experiments.
Keywords: Model Improvement, Model Teaching, Continuous DP, Gesture Recognition, Man-machine Interface.