适应度函数
支持向量机
人工智能
计算机科学
运动(音乐)
蹲下
分类
机器学习
核(代数)
身体素质
计算机视觉
物理医学与康复
遗传算法
物理疗法
数学
医学
哲学
组合数学
美学
作者
Atharian Rahmadani,Bima Sena Bayu Dewantara,Dewi Mutiara Sari
标识
DOI:10.1109/ies55876.2022.9888451
摘要
Based on computer vision technology, this research suggests an application to identify and assess a fitness practitioner’s movements. Several fitness movements such as lifting weights, squat jumps, and pull-ups that are very beneficial for health and body fitness become the main movement for body building. However, those kinds of activities may be very dangerous if done incorrectly. Based on the problem, we developed an application based on computer vision to recognize and correct the pose accuracy of fitness practitioners by using input in the form of videos that record the movements of fitness practitioners continuously. To categorize the many forms of fitness sport movements, this system uses the support vector machine (SVM) method. On the monitor screen, the classification results will be visible. The result shows that the accuracy of the system is 96.87% by using SVM with the Radial Basis Function (RBF) kernel type and can make corrections to four types of fitness movements with a testing accuracy of 90.62%.
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