Ethnic Traditional Sports Action Recognition Model Based on 3D-CNN and LSTM Visual Image Algorithms
In response to the problems of low accuracy and poor real-time performance in data recognition in traditional ethnic sports,this study combines virtual reality technology with motion capture technology based on 3D convolutional neural networks,and uses long short-term memory neural networks to capture temporal information in movements,proposing a traditional ethnic sports motion recognition model.The results indicate that the proposed traditional ethnic sports action recognition model converges to a function loss of around 0.021 and a recognition accuracy curve of 0.989 when the optimal DroPaout ratio is 0.6.Compared with other posture recognition systems,the model recognition accuracy has improved by more than 20%,with an error accuracy of less than 40mm.This method has achieved good recognition of movements in traditional ethnic sports such as Tai Chi,and has played a promoting role in the modern inheritance and training of traditional ethnic sports
ethnic traditional sportsaction recognitionmodeling3D-CNNLSTMvisual image algorithmsvirtual reality technology
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