Construction of street dance basic movement library based on artificial intelligence and analysis of teaching paths

Street dance has become a popular species worldwide. How to efficiently improve the teaching efficiency and effect of street dance has become an important issue that needs to be urgently solved. This paper proposes a method for constructing a street dance basic movement library and analyzing teaching paths based on artificial intelligence. Through data collection and processing, combined with action feature extraction and modeling, a basic action library for street dance was constructed. Teaching paths for different learning levels (beginners, advanced learners, and advanced learners) were designed to help beginners learn basic action knowledge, promote advanced learners to train their street dance skills, and enrich advanced learners' action performance styles. The effectiveness of the street dance teaching path and the street dance movement library was evaluated to verify the effectiveness of this method. It was proved that this approach could promote students' learning and improve the quality and efficiency of teaching in the process of street dance teaching.