Analysis of Main Movement Characteristics of Hip Hop Dance Based on Deep Learning of Dance Movements

Author:

Lu Rui1ORCID

Affiliation:

1. Sports Department, Guizhou University of Finance and Economics, Guiyang 550000, Guizhou, China

Abstract

In order to explore the main action characteristics of hip hop dance, a deep learning recognition system based on dance action is proposed. The network is based on convolution, pooling, and full connection calculation in a convolutional neural network (CNN). On the one hand, the pixel information in the video frame is extracted as the network input feature in the spatial domain. On the other hand, in the time domain, in order to better represent the change characteristics of video actions, optical flow information is introduced, and the optical flow vector change of pixels in DT time is calculated by the pyramid algorithm (LK) as the time domain convolution feature. In order to evaluate the performance of the network, this article takes the recognition of dance movements as an example to test the application of the algorithm. The test dataset contains 101 fully identified dance movements. The test results show that the proposed algorithm is 10.90% higher than F1 of inception V3, and the recognition accuracy is 10.85% and 5.27% higher than that of inception V3 and 3D-CNN networks, respectively. For the problems and difficulties brought by single-mode video action recognition, a multimodal action recognition method is introduced to achieve better results based on a large number of training data. Different depth networks have different characteristics. CNN network pays more attention to the relationship between local information, so it is suitable for image recognition and detection tasks. The RNN network is expanded in the time dimension, so it is suitable for the modal information related to similar videos. Therefore, based on multimodal information and a depth neural network, a depth feature extraction and fusion method for multimodal information is designed. Different methods of feature extraction and fusion are tried in the experiment, and the experimental results are analyzed. It proves that the deep learning and recognition of dance movement can effectively explore the main movement characteristics of hip hop dance.

Publisher

Hindawi Limited

Subject

General Mathematics,General Medicine,General Neuroscience,General Computer Science

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