The Method of Dance Movement Segmentation and Labanotation Generation Based on Rhythm

Cui, Changrui; Li, Junhuai; Du, Dandan; Tu, Pengjia; Cao, Ting

doi:10.1109/access.2021.3060103

Cited by 11 publications

(4 citation statements)

References 33 publications

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“…This format defines the human skeleton as a tree model composed of 18 joints. The skeletal node model of the human is demonstrated in Figure 4 [ 10 ].…”

Section: Methodsmentioning

confidence: 99%

Optimization of Choreography Teaching with Deep Learning and Neural Networks

Zhou

Tong

et al. 2022

Computational Intelligence and Neuroscience

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To improve the development level of intelligent dance education and choreography network technology, the research mainly focuses on the automatic formation system of continuous choreography by using the deep learning method. Firstly, it overcomes the technical difficulty that the dynamic segmentation and process segmentation of the automatic generation architecture in traditional choreography cannot achieve global optimization. Secondly, it is an automatic generation architecture for end-to-end continuous dance notation with access to temporal classifiers. Based on this, a dynamic time-stamping model is designed for frame clustering. Finally, it is concluded through experiments that the model successfully achieves high-performance movement time-stamping. And combined with continuous motion recognition technology, it realizes the refined production of continuous choreography with global motion recognition and then marks motion duration. This research effectively realizes the efficient and refined production of digital continuous choreography, provides advanced technical means for choreography education, and provides useful experience for school network choreography education.

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“…This format defines the human skeleton as a tree model composed of 18 joints. The skeletal node model of the human is demonstrated in Figure 4 [ 10 ].…”

Section: Methodsmentioning

confidence: 99%

Optimization of Choreography Teaching with Deep Learning and Neural Networks

Zhou

Tong

et al. 2022

Computational Intelligence and Neuroscience

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“…It is now vital to find a solution for the issue of how to better enable adolescents to engage in physical activity and psychological management. An AI-based system for teaching Latin dance to adolescents has developed in this setting [ 29 ]. Fig 6 displays the technologies and system features it possesses.…”

Section: Research Modelmentioning

confidence: 99%

“…It is now vital to find a solution for the issue of how to better enable adolescents to engage in physical activity and psychological management. An AI-based system for teaching Latin dance to adolescents has developed in this setting [29]. Compared with the traditional Latin dance teaching method, the adolescent health Latin dance teaching system based on AI technology has the following advantages.…”

Section: Teaching System and Optimization Of Adolescent Healthy Latin...mentioning

confidence: 99%

Design and implementation of adolescent health Latin dance teaching system under artificial intelligence technology

Liu,

Soh,

Dev Omar Dev

et al. 2023

PLoS ONE

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Since various dance teaching systems have attracted much attention with the development of Artificial Intelligence (AI) technology, this paper improves the recognition performance of Latin dance teaching systems by optimizing the action recognition model. Firstly, the object detection and action recognition technology under the current AI technology is analyzed, and the Two-stage object detection algorithm and One-stage object detection algorithm are evaluated. Secondly, the technologies and functions contained in the adolescent health Latin dance teaching system are described, including image acquisition, feature extraction, object detection, and action recognition. Finally, the action recognition algorithm is optimized based on object detection, and the rationality and feasibility of the proposed algorithm are verified by experiments. The experimental results show that the optimization algorithm can search the optimal feature subset after five iterations on Undefine Classes of 101 (UCF101) dataset, but it needs seven iterations on Human Motion Database 51 (HMDB51) dataset. Meanwhile, when using support vector machine classifier, the optimization algorithm can achieve the highest accuracy of motion recognition. Regressive Function, Multinomial Naive Bayes and Gaussian Naive Bayes Algorithms have lower prediction delay, as low as 0.01s. Therefore, this paper has certain reference significance for the design and implementation of adolescent health Latin dance teaching system.

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“…It is widely used in recording and teaching dance movements [1] because it can accurately and conveniently record and analyze all human movements. It is indispensable for the dissemination and communication of culture [2]. As a result, using labanotation as a method of recording is extremely beneficial to the preservation and transmission of Chinese traditional folk dance.…”

Section: Introductionmentioning

confidence: 99%

A Motion Capture Data-Driven Automatic Labanotation Generation Model Using the Convolutional Neural Network Algorithm

Jiang

Yang

2022

Wireless Communications and Mobile Computing

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All human movements can be effectively represented with labanotation, which is simple to read and preserve. However, manually recording the labanotation takes a long time, so figuring out how to use the labanotation to accurately and quickly record and preserve traditional dance movements is a key research question. An automatic labanotation generation algorithm based on DL (deep learning) is proposed in this study. The BVH file is first analyzed, and the data are then converted. On this foundation, a CNN (convolutional neural network) algorithm for generating the dance spectrum of human lower-limb movements is proposed, which is very good at learning action space information. The algorithm performs admirably in terms of classification and recognition. Finally, a spatial segmentation-based automatic labanotation generation algorithm is proposed. To begin, every frame of data is converted into a symbol sequence using spatial law, resulting in a very dense motion sequence. The motion sequence is then regulated according to the minimum beat of motion obtained through wavelet analysis. To arrive at the final result, the classifier is used to determine whether each symbol is reserved or not. As a result, we will be able to create more accurate dance music for simple human movements.

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The Method of Dance Movement Segmentation and Labanotation Generation Based on Rhythm

Cited by 11 publications

References 33 publications

Optimization of Choreography Teaching with Deep Learning and Neural Networks

Optimization of Choreography Teaching with Deep Learning and Neural Networks

Design and implementation of adolescent health Latin dance teaching system under artificial intelligence technology

A Motion Capture Data-Driven Automatic Labanotation Generation Model Using the Convolutional Neural Network Algorithm

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