Real-Time Recognition of Selected Karate Techniques Using GDL Approach
In this paper will be presented a new approach for recognition and interpretation of several karate techniques used specially defined Gesture description language (GDL). The novel contribution of this paper is validation of our new semantic Gesture Description Language classifier on several basic Karate techniques recorded with set of Kinect devices. We also present the calibration procedure that enables integration of skeleton data from set of tracking devices into one skeleton what eliminates many segmentation and tracking errors. The data set for our research contains 350 recorded sequences of qualifies professional sport (black belt) instructor, and master of Okinawa Shorin-ryu Karate. 83% of recordings were correctly classified. The whole solution runs in real-time and enables online and offline classification.
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