An Efficient and Compact Review of Face Recognition Techniques

Pallav Borisagar, Smeet Jani, Yash Agrawal, R. Parekh
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引用次数: 2

Abstract

Face detection deals with the specified object(face) within the given database. Several algorithms have been de-fined by different researchers for face recognition. Research, technology advancement and applications incorporating face recognition over the last few decades have grown enormously. It is growing as one of the profound and exciting research fields. Some of the practical and efficient algorithms for face recognition are Principal Component Analysis (PCA), Artificial Neural Network (ANN), Support Vector Machine (SVM), Feature based approach, Gabor wavelet, GPU based approach, 3D model-based face recognition, Linear Discriminant Analysis (LDA) and Using Facial Symmetry. Face recognition is a multidimensional field. Different algorithms give different performances in different situations like illumination, noise, pose and disgiuse change. All the aforementioned techniques are described briefly in this paper so as to give the general idea. The main focus of the paper is to bring all the different techniques at the same place and make it easy to review them.
高效紧凑的人脸识别技术综述
人脸检测处理给定数据库中的指定对象(人脸)。不同的研究人员已经定义了几种人脸识别算法。在过去的几十年里,人脸识别的研究、技术进步和应用都有了很大的发展。它正在成长为一个深刻而令人兴奋的研究领域。一些实用和有效的人脸识别算法有主成分分析(PCA)、人工神经网络(ANN)、支持向量机(SVM)、基于特征的方法、Gabor小波、基于GPU的方法、基于3D模型的人脸识别、线性判别分析(LDA)和利用面部对称性。人脸识别是一个多维领域。不同的算法在不同的情况下会有不同的表现,比如照明、噪音、姿势和伪装的变化。本文对上述所有技术进行了简要描述,以便给出总体思路。本文的主要重点是将所有不同的技术放在同一个地方,并使其易于审查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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