Development of Standardized Training Model and System for Dance Moves Based on Intelligent Teaching

With the continuous growth of artificial intelligence and information technology, online education is becoming increasingly popular, and more and more dancers are shifting from traditional offline learning to online training. In the process of dance practice, the occurrence of incorrect movements is difficult to avoid. If not detected and corrected in a timely manner, it may not only affect the expressiveness of the dance but also hinder the improvement of technical level. However, traditional human pose detection methods commonly suffer from low precision and low recognition rates in complex action recognition, making it hard to meet the high standard requirements of dance teaching. In response to this issue, this study designed and implemented for dance moves a standardized training system based on intelligent teaching. The system collects motion data of dancers through multi-sensor fusion technology and introduces a dance pose recognition and error correction model based on deep learning to achieve automatic recognition and accurate feedback of dance moves.