Research on Dynamic Sign Language Algorithm Based on Sign Language Trajectory and Key Frame Extraction
Yufei Yan, Zhijun Li, Tao Qunzhu, Chenyu Liu, Rui Zhang · 2019 IEEE 2nd International Conference on Electronics Technology (ICET) · 2019
Based on the depth information of Kinect, this paper studies the real-time dynamic sign language recognition algorithm and improves the dynamic time warping algorithm for the recognition of sign language trajectories. The traditional DTW algorithm is improved by using the path constraint of the relaxed endpoint, adding the lower bound function to cull part of the candidate sequence and terminate the match early. The key frames are extracted according to the sign language trajectory density, and the dynamic hand sign trajectory and key gesture type information are combined to obtain the final dynamic sign language recognition result. Experiments show that the average recognition rate of this method is more than 90%, which is better than the traditional DTW algorithm in recognition speed and recognition accuracy.