Research on the Application of IU-EKF Algorithm for Feature Extraction of Flute Performers Based on Deep Learning

Abstract

In order to achieve a more standardized teaching of flute playing gestures, a deep learning based application research on flute player hand shape feature extraction was proposed. Based on the theory of deep learning, a fusion network model based on VGG-16 was designed. The IU-EKF algorithm for deep learning was used to model, pose, learn, and train the hand shape of flute players. Experimental data analysis was conducted on the learning algorithm, and the experimental results showed that the model can extract gesture features for flute performance, whether on the back of the hand. The various angles of the upper and lower joints of the fingers have higher precision recognition than traditional methods. The feature extraction of flute gesture performance can also more effectively recognize the changes in different pitch angles of the gesture at different times, which has important reference value for the standardization of flute hand performance.