部分人脸识别:一项调查

M. Shafin, Rojina Hansda, Ekta Pallavi, D. Kumar, Sumanta Bhattacharyya, Sanjeev Kumar
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引用次数: 6

摘要

人脸识别在安全、图像增强或图像数据记录等实时应用领域是一个不断发展、具有挑战性和有趣的领域。在过去的几十年里,人们为了各种目的提出了大量的人脸识别算法,其中包括识别被遮挡的人脸,也称为部分人脸识别。在本文中,作者涵盖了用于识别不同场景下的部分人脸的主要技术和方法(PCA, LDA, SVM, ANN),如光照不足,姿态变化,人脸遮挡等。为了获得有效的结果,有各种各样的人脸数据库可供选择。本文还提到了这些数据库,以便更好地了解人脸图像的属性和条件。本文还介绍了部分人脸识别领域的一些最新进展,涵盖了CNN和深度学习等主题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Partial face recognition: a survey
Face recognition is an ever-growing, challenging and interesting area for the real-time application, such as security, image enhancement or image data recording. A large number of the face recognition algorithm are introduced in the last several decades for all kind of purposes, Including recognizing the occluded faces also known as Partial Face Recognition. In this paper, the author covered all the major techniques and methods (PCA, LDA, SVM, ANN) used for recognition the partial faces lying in different scenarios such as poor illumination pose variations, occlusion on faces, etc. For the effective result, there are various face databases available. These databases are also mentioned in this paper for a better understanding of face image properties and condition. The paper also introduced some of the recent advancement in the partial Face recognition field by covering topics such as CNN and DEEP learning.
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