人脸识别(英文)Face RecognitionPPT课件

人脸识别课件xx年xx月xx日CATALOGUE目录•人脸识别概述•人脸识别基础知识•人脸识别常用库和框架•人脸识别实际应用•人脸识别难点和挑战•人脸识别未来发展01人脸识别概述定义人脸识别是一种利用图像或视频数据进行人类身份识别的技术。

特点非接触性、非侵扰性、自然性、友好性和防伪能力。

人脸识别定义1人脸识别发展历程2320世纪60年代到80年代末，人脸识别技术开始起步。

起步阶段20世纪90年代到21世纪初，人脸识别技术开始快速发展和应用。

发展阶段21世纪初至今，人脸识别技术在算法、应用和标准化方面取得重大突破。

突破阶段人脸识别应用场景人脸识别技术应用于门禁系统，可以实现安全、方便、快捷的进出控制和管理。

门禁系统金融行业社会安全娱乐产业人脸识别技术可以用于金融行业中的身份认证、客户分群和风险评估等。

人脸识别技术可以用于社会安全领域的监控、追踪、查找和侦破案件等。

人脸识别技术可以用于娱乐产业中的特效制作、人脸替换、人脸合成和动画制作等。

02人脸识别基础知识基于深度学习的图像识别算法利用卷积神经网络（CNN）对图像进行特征提取，通过全连接层进行特征组合，实现图像分类和识别。

基于特征提取的图像识别算法利用传统图像处理技术，提取图像中的颜色、纹理、形状等特征，通过支持向量机（SVM）等分类器进行分类和识别。

图像识别算法利用神经网络对人脸进行特征提取，通过滑动窗口技术在图像中寻找人脸区域，并通过回归任务确定人脸的精确位置。

基于深度学习的人脸检测算法利用图像处理技术，对图像中的像素进行统计分析，得到人脸区域的特征表示，通过分类器进行人脸和非人脸的分类。

基于特征分析的人脸检测算法人脸检测算法基于深度学习的人脸特征提取算法利用卷积神经网络（CNN）对人脸进行特征提取，通过全连接层将特征进行组合和编码，得到人脸的特征向量。

基于传统机器学习的人脸特征提取算法利用图像处理技术，提取人脸的特征表示，如Gabor滤波器、LBP等，通过分类器进行人脸和非人脸的分类。

Face RecognitionToday ,I will talk about the study about face recognition.(第二页)As for the face recognition, we main talk about Two-Dimensional Techniques. The study is from The University of York ,Department of Computer Science , as for the date, it is September 2005.(第三页)We say the background.The current identification technology mainly include: fingerprint identification指纹识别, retina recognition视网膜识别, iris recognition虹膜识别, gait recognition步态识别, vein recognition静脉识别, face recognition人脸识别, etc.advantages优点：Compared with other identification methods, face recognition because of its direct, friendly and convenient features, users do not have any psychological barriers, is easy to be accepted by users.(第四页)Two-Dimensional Face Recognition is main about Face Localization.This consists of two stages: face detection（人脸检测）and eye localization（眼睛定位）. (第五页)Today we main study the research of eye localization.Eye localization is performed on the set of training images, which is then separated into two groups. By it, we can compute the average distance from the eye template. one is eye detection was successful (like the picture on), the dark picture means the detected eyes is closed to the eye template; and the other is failed(like the picture down), the bright points down means doesn’t close.(第六页)We do the research using the way: The Direct Correlation Approach（直接相关方法）.This is the way we make the study, you can have a little know about it. So I will not talk much about it.(第七页)This is the study’s main Experimental Process.It is divided into some groups, calculate the distance d, between two facial image vectors, we can get an indication of similarity. Then a threshold is used to make the final verification decision.(第八页)The result wo get the picture. By the picture, we gets an EER (能效比)of 25.1%, this means that one quarter of all verification operations carried out resulted in an incorrect classification. That also means Tiny changes cause the change of the location in image.(第九页)Conclusion: Two-Dimensional Techniques (we say 2D) is an important part in face recognition. It make a large use in face recognition. All in all, Face recognition is the easiest way to be accepted in the identification field.Thank you!。