3D human hand motion recognition system

The results of design and investigation on a human gesture recognition system, based on a Kinect sensor, are presented in this paper. In the presented research, we use a Kinect device as a 3D data scanner. Therefore, the 3D coordinates are calculated directly from depth images. The system's hardware description and computation method for 3D human gesture identification are presented in this study. Ten specific single hand motion gestures, repeated several times by seven different people were recorded and used in the experimentation. Gesture recognition and interpretation are performed by using a trained neural classifier in two ways. In the first way, single hand motion gestures are captured in free 3D space, while in the second one people's heads coordinates in 3D are used as reference points for recorded hand gestures. Such an approach provided easy adaptation and flexibility for gesture interpretation. The structure of the classifier was estimated through the trial and error approach.

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