The Role of the Combination of 3D Simulation Sequence Diagram and Video Motion Recognition Technology in Evaluating and Correcting Dancers' Dance Moves

Abstract

This paper combines the dance 3D space simulation sequence diagram with video motion recognition technology, filters, denoises, grays and background removal the collected dance video images, analyzes the motion characteristics of people in the sequence diagram, uses support vector machine to learn and train 3D space models, classifies and recognizes people's dance movements, and extracts 3D-SIFT and optical flow characteristics of various areas of human body. Form a three-dimensional space simulation sequence diagram, reduce and normalize the extracted features, get the feature vectors of various characters, and input them into the classifier to realize the recognition of dance movements. The results show that the combination of 3D-SIFT and optical flow can realize the dynamic change of human static information, the illumination invariance of SIFT features can make up for the illumination sensitivity of optical flow features, and the optical flow features can solve the instability problem of determining the key points of SIFT features.