Changes of Dance Sports in Air Equipment Dance Performance Using Convolutional Neural Network

Abstract

Dance is an artistic form that relies on human body to interpret the beauty. The expression of the character image in dance works through the display of the actor’s limb language and their expression of intrinsic emotions, making dance works aesthetic and delivering delicate emotions and profound ideas. This article aims to study the change of dance form in the air equipment dance performance by convolutional neural network technology. This paper also proposes to track the position and scale of the dancer in convolutional neural network. When estimating the position and scale of the dancer, the discriminant correlation filter is used to obtain a training sample around the initial area. The experimental results show that the recognition rate of HOG characteristics in the combination of the follower and the combination of the inner flower was 42.8%, 40%, respectively, which was 3.33%, 29.2% higher than the combination of the flower. At the same time, only the identification rate of 53.3% in this paper in the combination of the inner flowers was lower than 60% of the reference method. The algorithm herein can maintain a certain identification for complicated dance actions, and it is still able to ensure a certain accuracy in the case of confusion in the background and target. The effectiveness of this action recognition algorithm for dance action recognition algorithm is verified.