Design of Gesture Recognition Algorithm Based on Convolutional Neural Network
In response to the pain points of small range and weak robustness of sensors in gesture recogni-tion,the MediaPipe machine learning framework is used to traverse the captured gesture images in real-time,and a convolutional neural network is used for Gaussian smoothing filtering.Combined with a palm model of 21 feature joint points,fingertip movements are classified based on Euclidean distance discrimi-nation threshold and individual finger curvature,and real-time mapping between fingertips and model fea-ture points is established through coordinate relationships.According to the test,the accuracy of gesture recognition in the target area has reached 98％,and the accurate recognition of operation gestures such as control volume is realized.
万方数据
维普
