文章基本信息

标题：Gender Recognization & Age Prediction
本地全文：下载
作者：Mr. Raghvendra ; Prof.Sandeep Sahu
期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2014
卷号：3
期号：9
页码：7968-7973
出版社：IJECS
摘要：over the recent years, a great deal of effort has been made to age estimation & gender recognization from face images. It hasbeen reported that age can be accurately estimated under controlled environment such as frontal faces, no expression, and static lightingconditions. However, it is not straightforward to achieve the same accuracy level in real-world environment because of considerablevariations in camera settings, facial poses, and illumination conditions. In this paper, we apply a recently-proposed machine learningtechnique called covariate shift adaptation to alleviating lighting condition change between laboratory and practical environment.Through real-world age estimation experiments, we demonstrate the usefulness of our proposed method.
关键词：Face Detection; Skin Color Segmentation; Face;Features extraction; Features recognization; Fuzzy rules