Movement Tracking Detection of Break Dance Based on Deep Learning

Abstract

To accurately detect the movements of break dance, a movement detection strategy based on improved SSD is proposed. Among them, in order to reduce the calculation amount of traditional SSD, MobileNet_V2 network is used to replace the traditional VGG backbone network, and then the mutex loss function is introduced to weaken the interference of overlapping movements on detection. Finally, the test is carried out in the data set. The results show that after optimization by Loss function, the detection of the model is more accurate in the case of overlapping targets. The accuracy of the model on the test set is 93.4%, and the recall rate is 91.6%, which indicates that the proposed detection network model has a good effect on movement tracking capture, and it can be used in the movement tracking detection of break dance.