{"title":"Dance Creation Based on the Development and Application of a Computer Three-Dimensional Auxiliary System","authors":"L X Gao","doi":"10.5750/ijme.v1i1.1367","DOIUrl":null,"url":null,"abstract":"A three-dimensional auxiliary system serves as a foundational framework for spatial analysis and modeling in various fields. This system serves as a fundamental tool for visualizing and manipulating three-dimensional data, allowing researchers, designers, and engineers to accurately represent and analyze complex structures and environments. Dance creation is a multifaceted artistic process that involves choreographing movements, sequences, and gestures to convey ideas, emotions, and narratives through bodily expression. This paper uses the advanced automated application model for the dance creation with the 3D-auxiliary system for the choreography. The constructed model incorporates statistically integrated Principal Component Analysis (PCA) for the computation of features in the dance creation movement prediction. Finally, the estimation of the statistically integrated PCA model is applied over neural network modeling for the classification of features in the dance creation. With the estimated PCA model values statistical correlation between the PCA features are estimated and classified for the different dance types. The examination is based on the classification of dance movement dynamics, patterns, and stylistic elements for the dance creation. Simulation estimation demonstrated that a constructed statistical 3D auxiliary system was effectively involved in the dance movement prediction with the classification of features through a neural network for the dance movement prediction. The PCA model uses the 5 features to evaluate the auxiliary points of the dance movement in the reference human video. Through the analysis of the PCA features with the statistical values the outline sketch of the dance is framed and dance movement are created.","PeriodicalId":50313,"journal":{"name":"International Journal of Maritime Engineering","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Maritime Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.5750/ijme.v1i1.1367","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MARINE","Score":null,"Total":0}
引用次数: 0
Abstract
A three-dimensional auxiliary system serves as a foundational framework for spatial analysis and modeling in various fields. This system serves as a fundamental tool for visualizing and manipulating three-dimensional data, allowing researchers, designers, and engineers to accurately represent and analyze complex structures and environments. Dance creation is a multifaceted artistic process that involves choreographing movements, sequences, and gestures to convey ideas, emotions, and narratives through bodily expression. This paper uses the advanced automated application model for the dance creation with the 3D-auxiliary system for the choreography. The constructed model incorporates statistically integrated Principal Component Analysis (PCA) for the computation of features in the dance creation movement prediction. Finally, the estimation of the statistically integrated PCA model is applied over neural network modeling for the classification of features in the dance creation. With the estimated PCA model values statistical correlation between the PCA features are estimated and classified for the different dance types. The examination is based on the classification of dance movement dynamics, patterns, and stylistic elements for the dance creation. Simulation estimation demonstrated that a constructed statistical 3D auxiliary system was effectively involved in the dance movement prediction with the classification of features through a neural network for the dance movement prediction. The PCA model uses the 5 features to evaluate the auxiliary points of the dance movement in the reference human video. Through the analysis of the PCA features with the statistical values the outline sketch of the dance is framed and dance movement are created.
期刊介绍:
The International Journal of Maritime Engineering (IJME) provides a forum for the reporting and discussion on technical and scientific issues associated with the design and construction of commercial marine vessels . Contributions in the form of papers and notes, together with discussion on published papers are welcomed.