Eye detection and tracking in video streams

A. Fathi, M. T. Manzuri
{"title":"Eye detection and tracking in video streams","authors":"A. Fathi, M. T. Manzuri","doi":"10.1109/ISCIT.2004.1413921","DOIUrl":null,"url":null,"abstract":"This work presents a new method for eye detection in a sequence of video pictures. We first find the face region using the features of skin color, then the location of eye is determined by applying three cues on the detected face region. The first cue is the eye intensity and color, because the intensity of each eye region is relatively low and its color differs from the color of surrounding skin. The second cue is based on the position and size of eyes. The third cue is based on the convolution of the proposed eye-variance-filter with the eye-window candidates. After finding the precise location of the eye, it is tracked in a finite search window. We have evaluated and tested the presented system using different frame streams, and the results are encouraging.","PeriodicalId":237047,"journal":{"name":"IEEE International Symposium on Communications and Information Technology, 2004. ISCIT 2004.","volume":"231 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Symposium on Communications and Information Technology, 2004. ISCIT 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCIT.2004.1413921","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16

Abstract

This work presents a new method for eye detection in a sequence of video pictures. We first find the face region using the features of skin color, then the location of eye is determined by applying three cues on the detected face region. The first cue is the eye intensity and color, because the intensity of each eye region is relatively low and its color differs from the color of surrounding skin. The second cue is based on the position and size of eyes. The third cue is based on the convolution of the proposed eye-variance-filter with the eye-window candidates. After finding the precise location of the eye, it is tracked in a finite search window. We have evaluated and tested the presented system using different frame streams, and the results are encouraging.
视频流中的眼球检测和跟踪
本文提出了一种新的视频图像序列眼睛检测方法。我们首先利用肤色特征找到人脸区域,然后在检测到的人脸区域上应用三个线索来确定眼睛的位置。第一个线索是眼睛的强度和颜色,因为每个眼睛区域的强度相对较低,它的颜色与周围皮肤的颜色不同。第二个线索是基于眼睛的位置和大小。第三个线索是基于所提出的眼睛方差滤波器与眼窗候选图像的卷积。在找到眼睛的精确位置后,它会在有限的搜索窗口中被跟踪。我们使用不同的帧流对系统进行了评估和测试,结果令人鼓舞。
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