计算机与现代化Issue(3)：26-29,4.DOI:10.3969/j.issn.1006-2475.2018.03.005
基于神经网络的人体动作识别方法
Human Activity Recognition Method Based on Neural Network
摘要
Abstract
Human activity recognition has always been paid attention to the field of computer vision.In this paper,a weighted recognition method based on neural network is presented to improve the accuracy of human activity recognition.Firstly,the ViBe algorithm is used to extract the foreground of human activity,and the center of gravity of the foreground is calculated.Secondly, the Fourier descriptor is obtained by the Fourier transform of the outline distance center of gravity.Finally,a weighted recognition method based on neural network is used to classify the Fourier descriptor.The experimental results show that the recognition rate of this method is more than 89%.关键词
动作识别/神经网络/傅里叶描述子/ViBe/加权识别Key words
activity recognition/neural network/Fourier descriptor/ViBe/weighted recognition分类
信息技术与安全科学引用本文复制引用
董哲宇,汪千军,李万杰,周波..基于神经网络的人体动作识别方法[J].计算机与现代化,2018,(3):26-29,4.基金项目
国家自然科学基金资助项目(41401445) （41401445）
安徽省大学生创新创业训练基金资助项目(2016CXCYS111) （2016CXCYS111）
