An Online Arrangement Method of Difficult Actions in Competitive Aerobics Based on Multimedia Technology

Li Li,Chi-Hua Chen

doi:10.1155/2021/9968401

Abstract

In accordance with the development trend of competitive aerobics’ arrangement structure, this paper studies the online arrangement method of difficult actions in competitive aerobics based on multimedia technology to improve the arrangement effect. RGB image, optical flow image, and corrected optical flow image are taken as the input modes of difficult action recognition network in competitive aerobics video based on top-down feature fusion. The key frames of input modes in competitive aerobics video are extracted by using the key frame extraction method based on subshot segmentation of a double-threshold sliding window and fully connected graph. Through forward propagation, the score vector of video relative to all categories is obtained, and the probability score of probability distribution is obtained after normalization. The human action recognition in competitive aerobics video is completed, and the online arrangement of difficult action in competitive aerobics is realized based on this. The experimental results show that this method has a high accuracy in identifying difficult actions in competitive aerobics video; the online arrangement of difficult actions in competitive aerobics has obvious advantages, meets the needs of users, and has strong practicability.

Highlights

Competitive aerobics is a kind of sport that can perform continuous, complex, and high-intensity complete sets of movements with music accompaniment
As the main manifestation of the difficulty characteristics of competitive aerobics, the selection, arrangement, and completion quality of difficult action directly affect the quality of competitive aerobics. erefore, it is important to study the scientific and reliable online arrangement method of difficult actions in competitive aerobics [1, 2]
Is paper studies the online arrangement method of difficult actions in competitive aerobics based on multimedia technology. e recognition method of difficult actions in competitive aerobics video based on top-down feature fusion is used to accurately identify the human movements in competitive aerobics video and make online arrangement of difficult actions in competitive aerobics on this basis. e experimental results can verify the effectiveness and rationality of this method, which provides a new research direction to promote the technical level of competitive aerobics in China. e specific contributions of this paper include the following: (1) Transplant research results in the field of artificial intelligence into computer-aided online arrangement actions

Summary

Introduction

Competitive aerobics is a kind of sport that can perform continuous, complex, and high-intensity complete sets of movements with music accompaniment. E high-level feature map in each level constitutes the feature pyramid of the deep convolution neural network, and the feature map in the feature pyramid is taken as the feature map to be fused of the competitive aerobics video difficulty action recognition method based on top-down feature fusion [15,16,17]. E difficult action recognition network of competitive aerobics video based on top-down feature fusion adopts a dual-stream network structure, in which an RGB image is the input mode of the space stream network and optical flow image or correction optical flow image is the input mode of the time stream network. The main limitation of our proposal is that it needs a huge computation space, which indicates that our proposal has a strong requirement for computation and it may not be easy to realize

Result

80 RGB image

Findings

Conclusions