Individual Soldier Gesture Intelligent Recognition System
Depeng Zhu, Ranran Wei, Weida Zhan, Ziqiang Hao · 2019 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS) · 2019
In order to solve the problem that the combatants cannot communicate face to face while performing combat missions, a soldier identification intelligent recognition system was designed. First, the system performs data normalization and endpoint detection on the collected gesture information. Then, feature extraction of the processed data such as mean, peak-to-peak and root mean square values in the time domain. Finally, the dynamic time warping (DTW) algorithm is used to calculate the similarity between the test gesture and the template gesture for the extracted feature parameters, and then the recognition result is obtained. The experimental results show that the system has the characteristics of high recognition accuracy, fine real-time performance and strong adaptability to individual differences. Therefore, it is suitable for gesture recognition and communication when performing combat missions.