The paper presents enhancements and innovative solutions of the proposed in  algorithms for fingers tracking and hand gesture recognition based on new defined features describing hand gestures and exploiting new-tracked tip and thumb joints from Kinect v2 sensor. Dynamic Time Warping (DTW) algorithm is used for gestures recognition. We increased its accuracy, scale and rotational invariance by defining new 3D featuring angles describing gestures and used for training a gesture database. 3D positions for fingertips are extracted from depth sensor data and used for calculation of featuring angles between vectors. The provided by Kinect v2 3D positions for thumb, tip and hand joints also participates during the phases of recognition. A comparison with the latest published approach for finger tracking has been performed. The feasibility of the algorithms have been proven by real experiments.
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