The Art of Dance from the Perspective of Artificial Intelligence

Abstract

With the continuous improvement of artificial intelligence application level, computer data processing technology has gradually become the main and classic auxiliary technology application method in the daily work and life of the majority of society members. This article is based on artificial intelligence technology, using computer animation technology, combining artificial intelligence, computer music and graphics disciplines, to show the musical image in the virtual dance of characters, involving the analysis and recognition of musical elements, the establishment of character models, and motion control And other issues. This paper explores the Hidden Markov Model (IIMM, HiddenMarkovModel) model characteristics and algorithm training methods, and proposes an improved HMM training method model algorithm to identify common dance movement models and the control and synthesis of basic dance gestures. This system uses animation as a virtual dance character to show more dance artistic movements for the issues related to the display and scoring of dance movements. Based on the dance movement recognition algorithm and other related algorithms (such as score and error judgment algorithm, error reduction algorithm, etc.), this paper constructs a set of dance movement technical feature statistics and dance movement training. This system realizes the technical statistics and dance training of dance competitions. Two major functions. The above research solves the technical problems of software and hardware engineering from data collection to algorithm programming, and provides a functional platform for intelligent analysis and auxiliary training of dance art, which can be promoted and applied to more professional dancers and dance teachers, thereby accumulating a large amount of data and refining Produce more technical index parameters in line with the rules of dance art, and finally form a set of professional products for dance art intelligence analysis and auxiliary training.