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A review of the comparative studies on traditional and intelligent face recognition methods

机译：传统与智能面识别方法比较研究综述

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The birth of face recognition technology began in the 1960s, and it has experienced a general development process: based on face structure features (1970-1990), statistical features (1991-2000), big data and complex algorithms (2001-present). Among them, the first phase of face recognition technology is mainly to establish a grayscale image model through studying facial features, and at the same time, it can not complete the automatic recognition. In the second stage, multi-dimensional feature vectors are adopted to represent facial features, and previous empirical knowledge should be used for judgment. With the development of artificial intelligence, modern face recognition technology integrates artificial intelligence, machine learning, image processing and other technologies to study the face recognition problems facing with real conditions.This paper will summarize, analyze and discuss some traditional face recognition algorithms and current typical facial recognition technology based on artificial intelligence algorithm, and through the study on facial model building, facial feature representation, algorithm accuracy and other influencing factors, the advantages and disadvantages of each face recognition algorithm when applied to various fields will be analyzed, and then these algorithms will be evaluated and prospected.
机译：人脸识别技术的诞生始于20世纪60年代，它已经历了一个总的发展过程：基于人脸结构特点（1970-1990），统计特征（1991- 2000年），大数据和复杂的算法（2001年至今）。其中，人脸识别技术的第一阶段主要是通过学习五官建立了灰度图像模式，并在同一时间，它不能完成自动识别。在第二阶段中，多维特征向量被采用来表示面部特征，和以前的经验知识应该用于判断。随着人工智能技术的发展，现代的脸部识别技术集成人工智能，机器学习，图像处理等技术的研究与实际conditions.This纸面临将总结，分析和讨论一些传统的人脸识别算法的面部识别的问题和当前的典型基于面部识别技术对人工智能算法，并通过面部模型构建，人脸特征表示，算法精确度等影响因素的研究，当应用到各个领域的优势和各人脸识别算法的优缺点进行分析，然后将这些算法将被评估和展望。

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