Human Gait Recognition using Deep Convolutional Neural Network

P. Nithyakani, A. Shanthini, Godwin Ponsam
{"title":"Human Gait Recognition using Deep Convolutional Neural Network","authors":"P. Nithyakani, A. Shanthini, Godwin Ponsam","doi":"10.1109/ICCCT2.2019.8824836","DOIUrl":null,"url":null,"abstract":"A human acknowledgment and recognizable proof is viewed these days as an essential field of research. The most unique parts of human are the ear, odor, heartbeat, voice, the iris, periocular portion of eye, fingerprint, gait, sweat, face, etc,. Without the human interaction to identify a person is quite challenging with low resolution images. Gait recognition is one of the biometric technology which can be used to identify people without their knowledge. The proposed system uses Deep Convolutional Neural Network to extract the gait features of a person by training the neural network architecture with Gait Energy Image.","PeriodicalId":445544,"journal":{"name":"2019 3rd International Conference on Computing and Communications Technologies (ICCCT)","volume":"42 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 3rd International Conference on Computing and Communications Technologies (ICCCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCT2.2019.8824836","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

Abstract

A human acknowledgment and recognizable proof is viewed these days as an essential field of research. The most unique parts of human are the ear, odor, heartbeat, voice, the iris, periocular portion of eye, fingerprint, gait, sweat, face, etc,. Without the human interaction to identify a person is quite challenging with low resolution images. Gait recognition is one of the biometric technology which can be used to identify people without their knowledge. The proposed system uses Deep Convolutional Neural Network to extract the gait features of a person by training the neural network architecture with Gait Energy Image.
基于深度卷积神经网络的人体步态识别
如今,人类的承认和可识别的证据被视为一个重要的研究领域。人类最独特的部分是耳朵、气味、心跳、声音、虹膜、眼周部分、指纹、步态、汗水、面部等。在没有人类互动的情况下,用低分辨率的图像识别一个人是相当具有挑战性的。步态识别是一种生物特征识别技术,可以在人不知情的情况下对其进行识别。该系统采用深度卷积神经网络,通过步态能量图像训练神经网络结构,提取人的步态特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信