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Sang-Woon KIM Ji-Young OH Shin TANAHASHI Yoshinao AOKI
In order to investigate the possibility of avatar communication using sign-language, in this paper, we develop a sign-language chatting system on the Internet using CG aniamtion techniques between Korea and Japan. We construct the system in server-client architecture, where images of Korean or Japanese sign-language are analyzed into a series of parameters for sign-language animation by server. We transmit the parameters, which are text data instead of images or their compression, to clients and regenerate the corresponding CG animation using the received data. The chatting system is implemented with Visual C++ 5.0 on Windows platforms. Experimental results show that the sign-language could be used as a communication means between avatars of different languages.
Sang-Woon KIM Jong-Woo LEE Yoshinao AOKI
The sign-language can be used as a communication means between avatars having no common language. As a trial to overcome the linguistic barrier, we have previously developed a 2D model-based sign-language chatting system between Korean and Japanese on the the Internet. In that system, there have been some problems to be solved for natural animation and real-time transmission. In this paper, we employ a 3D character model for stereoscopic gestures in the sign-language animation. We also utilize CG animation techniques which use the variable number of frames and a cubic spline interpolation in order to generate realistic gestures. For real-time communication, on the other hand, we make use of an intelligent communication method on a client-server architecture. We implement a preliminary communication system with Visual C++ 5.0 and Open Inventor on Windows platforms. Experimental results show a possibility that the system could be used for avatar communications between different languages.
Sang-Woon KIM Seong-Hyo SHIN Yoshinao AOKI
We present experimental results for a structural learning method of feed-forward neural-network classifiers using Principal Component Analysis (PCA) network and Species Genetic Algorithm (SGA). PCA network is used as a means for reducing the number of input units. SGA, a modified GA, is employed for selecting the proper number of hidden units and optimizing the connection links. Experimental results show that the proposed method is a useful tool for choosing an appropriate architecture for high dimensions.