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Erschienen in: Cluster Computing 2/2019

08.03.2018

Automatic generation algorithm analysis of dance movements based on music–action association

verfasst von: Yun He, Quancheng Zhang

Erschienen in: Cluster Computing | Sonderheft 2/2019

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Abstract

With the rapid development of intelligent algorithm technology and big data technology, the dance is more and more urgent to get accurate analysis of optimization algorithm. It not only achieves the fusion of music and movement for the driven motion which provides a platform for integration, but also uses the optimization algorithm to realize an important project which produces the progress in the dance, the analysis of the dance is based on the generation method of creative methods. This paper designs and implements the automatic generation algorithm of genetic algorithm which is based on the basic design idea of dance movements, the design will be the triangle program as a typical example, and it’s generating test case as much as possible to complete path coverage in the specified range of data and input data. The experimental data shows that the algorithm generates test case which can not only complete the preset target path, and be able to complete a full. The generation of traversal target path meeting the required choreography. At the same time, the algorithm can coordinate the path of music and action to the greatest extent, and this algorithm lays the foundation for further integration of technology.

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Metadaten
Titel
Automatic generation algorithm analysis of dance movements based on music–action association
verfasst von
Yun He
Quancheng Zhang
Publikationsdatum
08.03.2018
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe Sonderheft 2/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-018-2205-0

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