A Survey on Facial Feature Extraction Techniques for Automatic Face Annotation

被引:0
作者
Patel, Twisha [1 ]
Shah, Bhumika [1 ]
机构
[1] Sarvajanik Coll Engn & Technol, Dept Comp Engn, Surat, Gujarat, India
来源
2017 INTERNATIONAL CONFERENCE ON INNOVATIVE MECHANISMS FOR INDUSTRY APPLICATIONS (ICIMIA) | 2017年
关键词
automatic image annotation; automatic face annotation; feature extraction; Speeded Up Robust Features; Scale Invariant Feature Transform; Convolutional Neural Network; Gabor Wavelet Transform; Eigenfaces; Local Binary Pattern;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Through the detonative development of web photo sharing websites and social network, enormous amount of pictures are uploaded and shared over the internet. Due to the great success of social web portals and social networks, web users are highly motivated to share their pictures over the internet and that permit other users to tag and comment on the pictures. Huge number of photos are shared over the social portals, some of these photos are tagged with appropriate names but many of them are unlabeled. So it becomes hard to understand the name of the individual from image if any random individual sees it. In order to overcome this problem automatic face annotation is used. Automatic face annotation is playing vital role in multimedia information. Automatic face annotation is method to identify human faces from image and assign appropriate human name. Face detection and face recognition are essential tasks in face annotation. In this paper, we discuss the phases of the automatic face annotation and surveyed various techniques of facial feature extraction.
引用
收藏
页码:224 / 228
页数:5
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