Dunhuang dance is an artistic treasure of traditional Chinese culture, with a long history and an important component of Dunhuang culture. Its digital preservation, display, and research are of great significance. To promote the digitalization process and development of Dunhuang dance, this study proposes to combine Dunhuang dance with 3D human pose estimation technology to construct a Dunhuang dance 3D action database. This database divides Dunhuang dance into 7 themes, 83 basic movements, and 16 long movements. Good results have been achieved in quantitative, qualitative, and manual evaluations, laying the foundation for the preservation, application, and development of Dunhuang dance; This provides new ideas for the research, promotion, and inheritance of Dunhuang culture. The future use of this database can be applied to generative artificial intelligence, digital exhibitions and performances of Dunhuang dance culture, education and research of Dunhuang dance, digital media and entertainment of Dunhuang dance, etc.

Dunhuang dance is an artistic treasure of Chinese traditional culture, which originates from Dunhuang mural paintings and is an important component of Dunhuang culture, and its digital preservation, display and research are of great significance. In order to promote the digitization process and development of Dunhuang Dance, this study proposes to combine Dunhuang Dance with three-dimensional human posture estimation technology to construct a three-dimensional movement database of Dunhuang Dance. For Dunhuang dance, the Dunhuang dance is divided, choreographed and captured according to character images, and a video action database of Dunhuang dance is constructed; for posture estimation, AMASS (Archive of Motion Capture as Surface Shapes) large-scale 3D human body motion capture dataset is used as the basis for generative adversarial training, and ResNet is used to extract the image features, and a gated recurrent network is used as the time encoder. The gated recurrent network is used as a time encoder, the parameter regressor regresses the SMPL parameter model, and the attention mechanism is used to amplify the degree of contribution of different frames of the sequence to give the probability of estimating the pose to be true or false on the basis of the human body's real motion AMASS, and then construct the Dunhuang dance 3D action database. This database divides Dunhuang dance into 7 themes, 83 basic movements and 16 long movements. Better results were obtained in quantitative, qualitative and manual evaluation, which laid the foundation for the preservation, application and development of Dunhuang dance; and provided new ideas for the research, promotion and inheritance of Dunhuang culture. Subsequent utilization of this database can be applied to generative artificial intelligence, digital exhibition and performance of Dunhuang dance culture, education and research of Dunhuang dance, and digital media and entertainment of Dunhuang dance.