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

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.

Research on dance teaching methods based on emotion recognition and emotion analysis

“…Dancers are able to explore new avenues for movement and self-expression through technology, the way it is through interactive applications, digital designs and experiences. Such enhances their creative practice and assist to develop greater connections with their profession [10][11]. Dancing instruction might be revolutionized by including emotion detection into the curriculum.…”

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

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [ 1 ]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process: Discrepancies in scope Discrepancies in the description of the research reported Discrepancies between the availability of data and the research described Inappropriate citations Incoherent, meaningless and/or irrelevant content included in the article Peer-review manipulation …”

“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”