An Adaptive Fuzzy Expert System for 3D Hand Motion Understanding
نویسندگان
چکیده
The Hand Motion Understanding (HMU) system recognises static and dynamic hand signs in Australian Sign Language (Auslan) by dealing with "fine grain" hand motion, such as configuration changes of fingers. The system consists of the 3D hand tracker and the adaptive fuzzy expert classifier. The hand tracker extracts 3D hand configuration data with 21 degrees-of-freedom (DOFs) from a visual motion sequence. Then the classifier recognises the changes of these 3D hand configuration data as a sign by using a fuzzy expert system. The fuzzy expert system is trained so that it can be adaptive to the errors caused by the 3D tracker and/or the slight motion variations of the individual signer. This paper presents the techniques used in the HMU system, and the recognition results of 22 static and dynamic signs.
منابع مشابه
3D Hand Tracker for Visual Sign Recognition
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