Recognition of Hand Gestures using Visible Light and a Probabilistic-based Neural Network

Julian L. Webber, Abolfazl Mehbodniya
{"title":"Recognition of Hand Gestures using Visible Light and a Probabilistic-based Neural Network","authors":"Julian L. Webber, Abolfazl Mehbodniya","doi":"10.1109/MENACOMM57252.2022.9998225","DOIUrl":null,"url":null,"abstract":"Gestures by hand are an effective and efficient means to interact with machines. We present a method for recognizing gestures via the analysis of interrupted light patterns using visible light. Utilizing low-cost and easily accessible components, the system can exploit existing light communications infrastructures. A probabilistic type neural network is applied to learn the sequence of obfuscated light patterns during movement of the hands. A novel preprocessing of the received light is introduced enabling the use of an accurate but low-complexity class of neural network.","PeriodicalId":332834,"journal":{"name":"2022 4th IEEE Middle East and North Africa COMMunications Conference (MENACOMM)","volume":"38 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 4th IEEE Middle East and North Africa COMMunications Conference (MENACOMM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MENACOMM57252.2022.9998225","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Gestures by hand are an effective and efficient means to interact with machines. We present a method for recognizing gestures via the analysis of interrupted light patterns using visible light. Utilizing low-cost and easily accessible components, the system can exploit existing light communications infrastructures. A probabilistic type neural network is applied to learn the sequence of obfuscated light patterns during movement of the hands. A novel preprocessing of the received light is introduced enabling the use of an accurate but low-complexity class of neural network.
基于可见光和概率神经网络的手势识别
手势是与机器交互的一种有效且高效的方式。我们提出了一种通过使用可见光分析中断光模式来识别手势的方法。利用低成本和易于获取的组件,该系统可以利用现有的光通信基础设施。应用概率型神经网络学习手部运动过程中混淆光模式的序列。介绍了一种新的接收光的预处理方法,可以使用一种精确但低复杂度的神经网络。
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:604180095
Book学术官方微信