A semantic‐driven generation of 3D Chinese opera performance scenes

The emergence of digital opera has enriched the stage performance of Chinese opera and expanded its dissemination means. However, the modern spread of traditional Chinese opera still faces hindrances. Digital opera performances require the generation of virtual scenes of the stages and characters. However, traditional virtual scene generation requires workers to build 3D models using modeling software and incorporate them into the performance scene. This article proposes a semantic‐based generation method for Chinese opera performance scenes. First, we analyze the scene description scripts to understand the elements in Chinese opera virtual scenes. The prior probability is subsequently used to learn the model placement rules in the opera scene model. A digital scene suitable for Chinese opera performance is then generated. The final results show that the method can generate natural and receptive opera digital performance scenes. This article's research ideas and achievements are conducive to the promotion of development of Chinese digital opera technology. They possess substantial significance to the inheritance and development of traditional Chinese opera art. This paper studies how to (semi‐)automatically generate a Chinese opera scene by inputting a descriptive text. It consists of text input, NLP, 3D model databases, and scene generation. The final results show that the method can generate natural and receptive opera digital performance scenes. This paper's research ideas and achievements are conducive to the promotion of development of Chinese digital opera technology.