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In this paper, we describe a system for recognizing both the isolated and continuous Chinese Sign Language (CSL) using two Cybergloves and two 3SAPCE-position trackers as gesture input devices. To get robust gesture features, each joint-angle collected by Cybergloves is normalized. The relative position and orientation of the left hand to those of the right hand are proposed as the signer position independent features. To speed up the recognition process, a fast match and a frame predictingdoi:10.1109/afgr.2000.840670 dblp:conf/fgr/MaGWW00 fatcat:4sfxkjqo7zckfo3kols6jd7aqa