Motion Capture Technology of Digital Animation Art Based on Machine Learning

Abstract

With the progress of society and the increasing development of science and technology, digital animation technology is also constantly innovating. Motion capture technology is widely used in film, television, media, and other fields and has the characteristics of the times. The use of motion capture technology in animation production can greatly improve the accuracy and professionalism of animation performances. It plays an important role in the development of animated character activities, especially in the creation of martial arts and professional dance performances. It uses motion capture technology to create animated character performances and composite effects. In this paper, four feature selection algorithms such as document frequency (DF), information gain (IG), mutual information (MI), and the chi-square test (CHI) were used, and they were used to capture action features and feature selection application steps based on the support vector machine (SVM) algorithm and the naive Bayes (NB) algorithm. The results of the experimental study showed that the TF-CHI algorithm in the improved algorithm had an accuracy rate of 89%, and the feature selection accuracy it made was better than the traditional algorithm. Therefore, the effectiveness of the animation motion capture technology based on the machine learning motion improvement algorithm has been confirmed.