人脸识别(英文)Face_Recognition
人脸识别英文专业词汇教学提纲
人脸识别英文专业词汇gallery set参考图像集Probe set=test set测试图像集face renderingFacial Landmark Detection人脸特征点检测3D Morphable Model 3D形变模型AAM (Active Appearance Model)主动外观模型Aging modeling老化建模Aging simulation老化模拟Analysis by synthesis 综合分析Aperture stop孔径光标栏Appearance Feature表观特征Baseline基准系统Benchmarking 确定基准Bidirectional relighting 双向重光照Camera calibration摄像机标定（校正）Cascade of classifiers 级联分类器face detection 人脸检测Facial expression面部表情Depth of field 景深Edgelet 小边特征Eigen light-fields本征光场Eigenface特征脸Exposure time曝光时间Expression editing表情编辑Expression mapping表情映射Partial Expression Ratio Image局部表情比率图(,PERI) extrapersonal variations类间变化Eye localization,眼睛定位face image acquisition 人脸图像获取Face aging人脸老化Face alignment人脸对齐Face categorization人脸分类Frontal faces 正面人脸Face Identification人脸识别Face recognition vendor test人脸识别供应商测试Face tracking人脸跟踪Facial action coding system面部动作编码系统Facial aging面部老化Facial animation parameters脸部动画参数Facial expression analysis人脸表情分析Facial landmark面部特征点Facial Definition Parameters人脸定义参数Field of view视场Focal length焦距Geometric warping几何扭曲Street view街景Head pose estimation头部姿态估计Harmonic reflectances谐波反射Horizontal scaling水平伸缩Identification rate识别率Illumination cone光照锥Inverse rendering逆向绘制技术Iterative closest point迭代最近点Lambertian model朗伯模型Light-field光场Local binary patterns局部二值模式Mechanical vibration机械振动Multi-view videos多视点视频Band selection波段选择Capture systems获取系统Frontal lighting正面光照Open-set identification开集识别Operating point操作点Person detection行人检测Person tracking行人跟踪Photometric stereo光度立体技术Pixellation像素化Pose correction姿态校正Privacy concern隐私关注Privacy policies隐私策略Profile extraction轮廓提取Rigid transformation刚体变换Sequential importance sampling序贯重要性抽样Skin reflectance model,皮肤反射模型Specular reflectance镜面反射Stereo baseline 立体基线Super-resolution超分辨率Facial side-view面部侧视图Texture mapping纹理映射Texture pattern纹理模式Rama Chellappa读博计划：1.完成先前关于指纹细节点统计建模的相关工作。
face_recognition人脸识别模块
face_recognition⼈脸识别模块face_recognition ⼈脸识别模块（安装之前，必须先安装dlib库）1. 基于dlib库，进⾏了⼆次封装。
号称是世界上最简洁的⼈脸识别库。
2. 训练数据集：是⿇省理⼯⼤学下属的学院利⽤13000多张照⽚为基础。
主要是以欧美⼈为主。
在 command line下安装模块时：F:\Python_AI\venv\Scripts> pip install face_recoginitonload_image_file : 加载要识别的⼈脸图像，返回Numpy数组，返回的是图⽚像素的特征向量（⼤⼩，⽅向）face_loctions: 定位图中⼈脸的坐标位置。
返回矩形框的location（top,right,bottom,left）face_landmarks: 识别⼈脸的特征点; 返回68个特征点的坐标位置（chin....）face_encodings: 获取图像中所有⼈脸的编码信息（向量）compare_faces: 由⾯部编码信息进⾏⾯部识别匹配。
#!/usr/bin/env python# !_*_ coding:utf-8 _*_import face_recognitionfrom PIL import Image, ImageDrawimport cv2# face_image = face_recognition.load_image_file('imgs/twis001.jpg')face_image = cv2.imread('imgs/twis001.jpg')face_marks_list = face_recognition.face_landmarks(face_image)pil_image = Image.fromarray(face_image)d = ImageDraw.Draw(pil_image)for face_marks in face_marks_list:facial_features = ['chin','left_eyebrow','right_eyebrow','nose_bridge','nose_tip','left_eye','right_eye','bottom_lip']for facial_feature in facial_features:# print("{}: 特征位置：{}".format(facial_feature, face_marks[facial_feature]))# d.line(face_marks[facial_feature], fill=(0, 255, 0), width=5)# d.point(face_marks[facial_feature], fill=(255, 0, 0))for p in face_marks[facial_feature]:print(p)cv2.circle(face_image, p, 1, (0, 255, 0), 1)cv2.imshow("images", face_image)cv2.imwrite("twis01.jpg",face_image)cv2.waitKey(0)cv2.destroyAllWindows()# pil_image.show()#!/usr/bin/env python# !_*_ coding:utf-8 _*_import face_recognitionfrom PIL import Image, ImageDraw, ImageFontimage_known = face_recognition.load_image_file('imgs/yangmi/yangmidanr00.jpg')image_unknown = face_recognition.load_image_file('imgs/yangmi/yangmihe02.jpg')image_known_encodings = face_recognition.face_encodings(image_known)[0]face_locations = face_recognition.face_locations(image_unknown)results = []for i in range(len(face_locations)):top, right, bottom, left = face_locations[i]face_image = image_unknown[top:bottom, left:right]face_encoding = face_recognition.face_encodings(face_image)if face_encoding:result = {}matches = face_pare_faces(face_encoding, image_known_encodings, tolerance=0.5) if True in matches:print('在未知图⽚中找到了已知⾯孔')result['face_encoding'] = face_encodingresult['is_view'] = Trueresult['location'] = face_locations[i]result['face_id'] = i + 1results.append(result)if result['is_view']:print("已知⾯孔匹配照⽚上的第{}张脸！".format(result['face_id']))pil_image = Image.fromarray(image_unknown)draw = ImageDraw.Draw(pil_image)view_face_locations = [i['location'] for i in results if i['is_view']]for location in view_face_locations:top, right, bottom, left = locationdraw.rectangle([(left, top), (right, bottom)], outline=(0, 255, 0), width=2)font = ImageFont.truetype("consola.ttf", 20, encoding='unic')draw.text((left, top - 20), "yangmi", (255, 0, 0), font=font)pil_image.show()# 可以试着⽤cv2来画框，和写字 puttext#!/usr/bin/env python# !_*_ coding:utf-8 _*_import face_recognitionimport cv2img_known = face_recognition.load_image_file("imgs/joedan/cows.jpeg")img_unkown = face_recognition.load_image_file("imgs/joedan/joedan01.jpg")face_encodings_known = face_recognition.face_encodings(img_known)face_encodings_unknow = face_recognition.face_encodings(img_unkown)[0]matches = face_pare_faces(face_encodings_known, face_encodings_unknow, tolerance=0.5) print(matches)locations = face_recognition.face_locations(img_known)print(locations)if True in matches:index = matches.index(True)match = locations[index]print(match)top, right, bottom, left = matchcv2.rectangle(img_known, (left, top), (right, bottom), (0, 0, 255), 2)cv2.imshow("images", img_known)cv2.waitKey(0)cv2.destroyAllWindows()。
单词recognition释义及用法
Recognition识别speech recognition systems 语音识别系统facial recognition 人脸识别短语：win recognition from sb.赢得(某人的)赞誉，博得(某人的)好评He has won wide recognition in the field of tropical medicine. 他在热带疾患这一医学领域里广获赞誉.Xinhuanet 2011-07-27 15:06标题Chinese synchronized（同步的）swimmers(花样游泳队员，synchronized swimming花样游泳) aim high at London OlympicsWith her(China's Japanese coach) instruction, Chinese swimmers have improved markedly in strength, technique and speed, and gradually won recognition from international judges.From the 2008 Summer Olympics in Beijing to the 2010 World Expo in Shanghai, and from China's rapid economic growth to its successful dealing with the latest global financial crisis, all of those feats won international recognition.短语：beyond recognition面目全非，完全改了模样，变化大得难以认出Local police said that several of the bodies recovered from the bus were burned beyond recognition, adding that they will have to be identified through DNA testing. 背景,北京-珠海的长途客车途经信阳时发生着火.短语：recognition and appreciation 肯定与欣赏承认Recognition helps funding Libyan opposition: U.S. official 2011-07-16 04:27:17 The recognition of Libya's opposition National Transitional Council (NTC) by the U.S. and other countries will enable it to have more funding from Libya's frozen assets, U.S. State Department spokesman Mark Toner said on Friday."The most important thing today is the recognition of the TNC(Transitional National Council) as the legitimate voice of the Libyan people," he （a seniorofficial for the Transitional National Council (TNC) ）sai d. 背景：利比亚问题联络小组15日在土耳其伊斯坦布尔开会，承认利比亚反对派“全国过渡委员会”为“合法政府”Li Guangdou, an analyst on brand competitiveness, said Chinese companies have greatly improved their manufacturing capacity during the past three decades, but they still lag their Western counterparts in brand promotion. It results in some Chinese customers having a higher recognition of foreign brands, even though many Chinese companies can also produce highquality goods," Li said on Wednesday. Li expects that the Da Vinci case will prompt Chinese consumers "to be more rational about foreign brands."背景:达芬奇家居事件。
Face Recognition(人脸识别)
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!。
关于人脸识别的英语短文----人脸识别是一把双刃剑
Face recognition is a double-edged swordFace recognition technology has become increasingly popular in recent years. It is a method of identifying individuals based on their facial features. With advancements in artificial intelligence, face recognition has become a powerful tool in various industries such as security, marketing, and law enforcement. One of the most common applications of face recognition technology is in security systems. Security cameras equipped with face recognition technology can identify individuals as they enter a building or access a restricted area. This technology can help prevent unauthorized access and reduce the risk of theft and other criminal activities.In marketing, face recognition technology is used to analyze consumer behavior. By analyzing the facial expressions and emotions of customers, businesses can gain valuable insights into their preferences and buying habits. This information can then be used to create targeted marketing campaigns that are more likely to resonate with the target audience.In law enforcement, face recognition technology is used to identify suspects and missing persons. Police departments use facial recognition technology to match photos of suspects to databases of known criminals or missing persons. This technology can help solve crimes and reunite missing persons with their families.Despite the many benefits of face recognition technology, there are also concerns about privacy and potential misuse of the technology. Critics arguethat face recognition technology could be used to monitor individuals without their knowledge or consent. There is also the potential for the technology to be used to discriminate against certain groups of people.In conclusion, face recognition technology has the potential to revolutionize various industries and improve security measures. However, it is important to consider the potential risks and ethical implications of the technology. As we continue to develop and implement this technology, it is crucial to ensure that it is used in a responsible and ethical manner.译文：人脸识别是一把双刃剑近年来，人脸识别技术越来越流行。
Python使用face_recognition人脸识别
Python使⽤face_recognition⼈脸识别Python 使⽤ face_recognition ⼈脸识别官⽅说明：⼈脸识别 face_recognition 是世界上最简单的⼈脸识别库。
使⽤ dlib 最先进的⼈脸识别功能构建建⽴深度学习，该模型准确率在99.38%。
Python模块的使⽤ Python可以安装导⼊ face_recognition 模块轻松操作，对于简单的⼏⾏代码来讲，再简单不过了。
Python操作 face_recognition API ⽂档：⾃动查找图⽚中的所有⾯部import face_recognitionimage = face_recognition.load_image_file("my_picture.jpg")face_locations = face_recognition.face_locations(image)# face_locations is now an array listing the co-ordinates of each face!还可以选择更准确的给予深度学习的⼈脸检测模型import face_recognitionimage = face_recognition.load_image_file("my_picture.jpg")face_locations = face_recognition.face_locations(image, model="cnn")# face_locations is now an array listing the co-ordinates of each face!⾃动定位图像中⼈物的⾯部特征import face_recognitionimage = face_recognition.load_image_file("my_picture.jpg")face_landmarks_list = face_recognition.face_landmarks(image)# face_landmarks_list is now an array with the locations of each facial feature in each face.# face_landmarks_list[0]['left_eye'] would be the location and outline of the first person's left eye.识别图像中的⾯部并识别它们是谁import face_recognitionpicture_of_me = face_recognition.load_image_file("me.jpg")my_face_encoding = face_recognition.face_encodings(picture_of_me)[0]# my_face_encoding now contains a universal 'encoding' of my facial features that can be compared to any other picture of a face! unknown_picture = face_recognition.load_image_file("unknown.jpg")unknown_face_encoding = face_recognition.face_encodings(unknown_picture)[0]# Now we can see the two face encodings are of the same person with `compare_faces`!results = face_pare_faces([my_face_encoding], unknown_face_encoding)if results[0] == True:print("It's a picture of me!")else:print("It's not a picture of me!")face_recognition ⽤法要在项⽬中使⽤⾯部识别，⾸先导⼊⾯部识别库，没有则安装：import face_recognition基本思路是⾸先加載圖⽚：# 导⼊⼈脸识别库import face_recognition# 加载图⽚image = face_recognition.load_image_file("1.jpg")上⾯这⼀步会将图像加载到 numpy 数组中，如果已经有⼀个 numpy 数组图像则可以跳过此步骤。
人脸识别英文专业词汇
gallery set参考图像集Probe set=test set测试图像集face renderingFacial Landmark Detection人脸特征点检测3D Morphable Model 3D形变模型AAM (Active Appearance Model)主动外观模型Aging modeling老化建模Aging simulation老化模拟Analysis by synthesis 综合分析Aperture stop孔径光标栏Appearance Feature表观特征Baseline基准系统Benchmarking 确定基准Bidirectional relighting双向重光照Camera calibration摄像机标定（校正）Cascade of classifiers级联分类器face detection 人脸检测Facial expression面部表情Depth of field 景深Edgelet 小边特征Eigen light-fields本征光场Eigenface特征脸Exposure time曝光时间Expression editing表情编辑Expression mapping表情映射Partial Expression Ratio Image局部表情比率图(,PERI) extrapersonal variations类间变化Eye localization,眼睛定位face image acquisition人脸图像获取Face aging人脸老化Face alignment人脸对齐Face categorization人脸分类Frontal faces 正面人脸Face Identification人脸识别Face recognition vendor test人脸识别供应商测试Face tracking人脸跟踪Facial action coding system面部动作编码系统Facial aging面部老化Facial animation parameters脸部动画参数Facial expression analysis人脸表情分析Facial landmark面部特征点Facial Definition Parameters人脸定义参数Field of view视场Focal length焦距Geometric warping几何扭曲Street view街景Head pose estimation头部姿态估计Harmonic reflectances谐波反射Horizontal scaling水平伸缩Identification rate识别率Illumination cone光照锥Inverse rendering逆向绘制技术Iterative closest point迭代最近点Lambertian model朗伯模型Light-field光场Local binary patterns局部二值模式Mechanical vibration机械振动Multi-view videos多视点视频Band selection波段选择Capture systems获取系统Frontal lighting正面光照Open-set identification开集识别Operating point操作点Person detection行人检测Person tracking行人跟踪Photometric stereo光度立体技术Pixellation像素化Pose correction姿态校正Privacy concern隐私关注Privacy policies隐私策略Profile extraction轮廓提取Rigid transformation刚体变换Sequential importance sampling序贯重要性抽样Skin reflectance model,皮肤反射模型Specular reflectance镜面反射Stereo baseline立体基线Super-resolution超分辨率Facial side-view面部侧视图Texture mapping纹理映射Texture pattern纹理模式Rama Chellappa读博计划：1.完成先前关于指纹细节点统计建模的相关工作。
人脸识别英文作文
人脸识别英文作文I think facial recognition technology is both fascinating and a little bit scary. It's amazing how a computer can analyze and identify a person's face with such accuracy. It's like something out of a sci-fi movie.The idea of being able to unlock your phone or access your bank account just by looking at a camera is pretty cool. It's convenient and feels like the future is already here.On the other hand, the thought of cameras everywhere being able to track and identify us at any time is a little unsettling. It feels like our privacy is being invaded, and it's hard to know who might have access to all that information.I also worry about the potential for misuse of facial recognition technology. It's easy to imagine how it could be used for surveillance or even discrimination. It'simportant to have regulations in place to protect people from these kinds of abuses.At the same time, there are also some really positive uses for facial recognition. For example, it can help law enforcement identify criminals or find missing persons. It can also be used for security in places like airports and government buildings.Overall, I think facial recognition technology has alot of potential, but it's important to proceed with caution. We need to balance the benefits with the potential risks and make sure that people's rights and privacy are protected.。
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Fundamentals
step 3 ) recognization process
After step2, the extracted feature of the input face is matched against those faces in the database; just like this pictuer, it outputs the result when a match is found.
Fundamentals
step 2 ) feature extraction for database at the same time for input image
Feature extraction can provide effective information .Like those pictures, a birthmark under the right eye is useful to distinguish that they are one person.
Face Recognition
Face Recognition step1
Fundamentals
step2
step3
Application
What is Face Recognition
An advance biometric identification technique A computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source.
Application
Face recognition to pay
Alibaba Group founder Jack Ma showed off the technology Sunday during a CeBIT event that would seamlessly scan users’ faces via their smartphones to verify mobile payments. The technology, called “Smile to Pay,” is being developed by Alibaba’s finance arm, Ant Financial.
Fundamentals
step 1 ) face detection
In this step, the system will check is input image a face or not?
face detection is a computer technology that identifies human faces in digital images. It detects human faces which might then be used for recognizing a particular face. This technology is being used in a variety of applications no