Enhancing User Experience with Human-Computer Interaction Technology: A Digital Terminal Application

The objective is to develop an accurate method for capturing and identifying complex gestures, with the aim of enhancing the user experience of digital media multimedia terminals.A dynamic gesture recognition system based on Leap Motion sensor and bidirectional long and short term memory network is designed.Gesture recognition, classification and control are realized by collecting and analyzing gesture data and combining with deep learning algorithm.The experimental results show that the recognition accuracy of model training set reaches 99%, test set reaches 97%, and the error converges to less than 0.2 in training set and less than 0.01 in test set.The model also shows high accuracy and low error in the craft language database.The dynamic gesture recognition system designed in this study provides users with more intelligent and convenient digital media multimedia terminal experience, and has broad application prospects in the dynamic gesture recognition multimedia terminal.