3D Hand Tracker for Visual Sign Recognition
نویسندگان
چکیده
The gesture recognition process, in general, may be divided into two stages: motion sensing, which extracts useful data from hand motion; and the classification process, which classifies the motion sensing data as gestures. We have developed the visionbased Hand Motion Understanding (HMU) system that recognises static and dynamic Australian Sign Language (Auslan) signs by extracting and classifying 3D hand configuration data from the visual input. The HMU system uses a combination of a 3D hand tracker for motion sensing, and an adaptive fuzzy expert system for classification. This paper explains the 3D hand tracker that extracts the changes in the 21 degrees-of-freedom parameters of the hand from a sequence of images. The tracker performance is successfully demonstrated by tracking the hand motions appearing in Auslan sign sequences.
منابع مشابه
Visual Sign Language Recognition
We have developed the Hand Motion Understanding (HMU) system that understands static and dynamic signs of the Australian Sign Language (Auslan). The HMU system uses a visual 3D hand tracker for motion sensing, and an adaptive fuzzy expert system for classification of the signs. This paper presents the hand tracker that extracts 3D hand configuration data with 21 degrees-of-freedom (DOFs) from a...
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The Hand Motion Understanding (HMU) system is a vision-based Australian sign language recognition system that recognises static and dynamic hand signs. It uses a visual hand tracker to extract 3D hand configuration data from a visual motion sequence, and a classifier that recognises the changes of these 3D kinematic data as a sign. This paper presents the HMU classifier that uses an adaptive fu...
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