Visual Sensing Human Motion Detection System for Interactive Music Teaching

The purpose is to study the interactive teaching mode of human action recognition technology in music and dance teaching under computer vision. The human action detection and recognition system based on a three-dimensional (3D) convolutional neural network (CNN) is established. Then, a human action...

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Autores principales:	Xunyun Chang, Liangqing Peng
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Technology (General) T1-995
Acceso en línea:	https://doaj.org/article/b0ac72d8863645c38a85c6dc0f19cc70
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spelling	oai:doaj.org-article:b0ac72d8863645c38a85c6dc0f19cc702021-11-29T00:56:44ZVisual Sensing Human Motion Detection System for Interactive Music Teaching1687-726810.1155/2021/2311594https://doaj.org/article/b0ac72d8863645c38a85c6dc0f19cc702021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/2311594https://doaj.org/toc/1687-7268The purpose is to study the interactive teaching mode of human action recognition technology in music and dance teaching under computer vision. The human action detection and recognition system based on a three-dimensional (3D) convolutional neural network (CNN) is established. Then, a human action recognition model based on the dual channel is proposed on the basis of CNN, and the visual attention mechanism using the interframe differential channel is introduced into the model. Through experiments, the performance of the system in the process of human dance image recognition based on the Kungliga Tekniska Högskolan (KTH) dataset is verified. The results show that the dual-channel 3D CNN human action recognition system can achieve high accuracy in the first few rounds of training after the frame difference channel is added, the error can be reduced quickly, and the convergence can start quickly; the recognition accuracy of the system on KTH dataset is 96.6%, which is higher than that of other methods; for 3×3×3 basic convolution kernel, the best performance of the classification network can be obtained by pushing forward 0.0091 seconds in the calculation. Thereby, the dual-channel 3D CNN recognition system has good human action recognition accuracy in the dance interactive teaching mode of music teaching.Xunyun ChangLiangqing PengHindawi LimitedarticleTechnology (General)T1-995ENJournal of Sensors, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology (General) T1-995
spellingShingle	Technology (General) T1-995 Xunyun Chang Liangqing Peng Visual Sensing Human Motion Detection System for Interactive Music Teaching
description	The purpose is to study the interactive teaching mode of human action recognition technology in music and dance teaching under computer vision. The human action detection and recognition system based on a three-dimensional (3D) convolutional neural network (CNN) is established. Then, a human action recognition model based on the dual channel is proposed on the basis of CNN, and the visual attention mechanism using the interframe differential channel is introduced into the model. Through experiments, the performance of the system in the process of human dance image recognition based on the Kungliga Tekniska Högskolan (KTH) dataset is verified. The results show that the dual-channel 3D CNN human action recognition system can achieve high accuracy in the first few rounds of training after the frame difference channel is added, the error can be reduced quickly, and the convergence can start quickly; the recognition accuracy of the system on KTH dataset is 96.6%, which is higher than that of other methods; for 3×3×3 basic convolution kernel, the best performance of the classification network can be obtained by pushing forward 0.0091 seconds in the calculation. Thereby, the dual-channel 3D CNN recognition system has good human action recognition accuracy in the dance interactive teaching mode of music teaching.
format	article
author	Xunyun Chang Liangqing Peng
author_facet	Xunyun Chang Liangqing Peng
author_sort	Xunyun Chang
title	Visual Sensing Human Motion Detection System for Interactive Music Teaching
title_short	Visual Sensing Human Motion Detection System for Interactive Music Teaching
title_full	Visual Sensing Human Motion Detection System for Interactive Music Teaching
title_fullStr	Visual Sensing Human Motion Detection System for Interactive Music Teaching
title_full_unstemmed	Visual Sensing Human Motion Detection System for Interactive Music Teaching
title_sort	visual sensing human motion detection system for interactive music teaching
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/b0ac72d8863645c38a85c6dc0f19cc70
work_keys_str_mv	AT xunyunchang visualsensinghumanmotiondetectionsystemforinteractivemusicteaching AT liangqingpeng visualsensinghumanmotiondetectionsystemforinteractivemusicteaching
_version_	1718407667189284864

Visual Sensing Human Motion Detection System for Interactive Music Teaching

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