Optimization of Image Recognition Technology for Dance Theatre Creation and Evaluation of Its Effectiveness

Dance is interpreted through human body movements, dance movements can express the thoughts and emotions of dancers, and whether the dance movements are standardized or not in the creation of dance drama determines the quality of the creation of dance drama. In this paper, with the support of artificial intelligence and information technology, based on image recognition technology, we carry out the optimization research of dance movement recognition for dance drama creation. In this study, the principle and process of image recognition technology are first studied in depth, and then the motion detection method for dance movements is analyzed considering the static state of the background of the dance drama. On this basis, the recognition optimization of dance movements is completed based on the deep convolutional embedding attention mechanism, and the evaluation method based on recognition optimization is proposed for the creation of dance drama. The embedding method in this paper improves 12% over the baseline method, with an OA of 98.65%, while the amount of participation and FLOPs increase slightly. And the score1 and score2 of this paper’s method are the highest, which indicates that this method obtains a high model accuracy while sacrificing less number of model parameters and computational complexity. In addition, the network model structure of this paper is more efficient compared to other network model results. In the recognition effect analysis, the correct recognition rate of six standard dance movements such as center of gravity transition, time step, square step, lock step, fixed step and others are above 80%, with high recognition accuracy and excellent model performance.