现代信息科技2023，Vol.7Issue(23)：73-78,82,7.DOI:10.19850/j.cnki.2096-4706.2023.23.016
基于OpenPose改进的老人摔倒检测算法
Improved Elderly Fall Detection Algorithm Based On OpenPose
摘要
Abstract
In order to avoid personal injuries caused by failure to provide timely medical assistance after an elderly fall,the study finds that elderly falls and timely warnings can reduce the damage and serious consequences of elderly falls.In order to improve the detection accuracy and real-time performance of the elderly fall detection algorithm,an improved elderly fall detection algorithm based on OpenPose is proposed.The algorithm proposes to replace some of its convolutional layers with the Depthwise Separable Convolution neural network type based on the OpenPose human skeleton information recognition network.The algorithm uses the Long Short-Term Memory Networks to detect falls of the elderly.The fall and related behavioural data are extracted from the URFall public dataset to enrich the home-made datasets.Experimental results show that the improved algorithm in this paper greatly improves the recognition accuracy of the system in discriminating falls.关键词
OpenPose/深度可分离卷积/长短期记忆神经网络/摔倒检测/深度学习Key words
OpenPose/Depthwise Separable Convolution/Long Short-Term Memory Network/fall detection/Deep Learning分类
信息技术与安全科学引用本文复制引用
胡昕,刘瑞安,黄玉兰..基于OpenPose改进的老人摔倒检测算法[J].现代信息科技,2023,7(23):73-78,82,7.基金项目
天津师范大学研究生科研创新项目(2022KYCX105Y) （2022KYCX105Y）
