搜索资源列表
createFaceEignDatabase
- 利用一个小样本人脸样本库创建数据库ar_test.mat中的训练样本数据和待测样本数据将生产的数据库文件.mat利用FDDL程序进行测试，分类；在程序最后先利用最短距离测试提取特征的效果本文利用SVD分解，并提取了每一幅图像的前3列特征向量（前三个主成分），共计3*200个特征向量，构成一个训练样本列元素最后的简单分类测试效果在90 ，区分度较好，能够适用于其他分类器实验..后续中，选取了第一主成分，发现识别率达到100 ；选取了前33个，反而低于了90 ，不知如何解释？-Using a sma
[first_author]_2014_Digital-Signal-Processing
- This study proposes a novel near infrared face recognition algorithm based on a combination of both local and global features. In this method local features are extracted from partitioned images by means of undecimated discrete wavelet transform
orl-LBP
- 这个是LBP人脸算法，对学习者有很好的帮助，关于人脸表情识别，这里是基于ORL人脸库。-This is the human face LBP algorithm, the learners have good help, on facial expression recognition, here is based on the ORL database.
diploscoremanager-28794
- Diplomacy Score and Tournament Manager C#.Net developers, at least 4 years experience implementing desktop application with access to Database and rules based engines. Desktop Software in C# to manage Face to face Diplomacy tournaments orga
first-review-report
- This project describes the problem of facial expression recognition in the field of computer vision. Firstly, the psychological background of the problem is presented. Then, the idea of facial expression recognition system (FERS) is outlined and the
sparse-representation-pdf
- This project describes the problem of facial expression recognition in the field of computer vision. Firstly, the psychological background of the problem is presented. Then, the idea of facial expression recognition system (FERS) is outlined and the
PCA
- 数据来源：ORL Database of Faces人脸数据库 其中同一个人的10张人脸图像为一组，共40组,图像大小为112x92 采用PCA算法实现对人脸的识别，当每组训练样本占70 时，识别准确率达到96.67 -Source: ORL Database of Faces face in which the same person 10 face images as a group, a total of 40 groups, image size of 112x92 using
FaceRecognition
- 本算法将进行人脸识别，首先进行人脸定位检测，然后根据数据库里给的标签进行人脸识别，将人脸的信息显示在人脸旁边。本算法能取得较好的效果。(The algorithm will perform face recognition, first face detection, and then according to the database to the label for face recognition, the face of the information displayed next to
FaceRecog_bin
- 人脸识别，可自建库，并将语句转换成exe，可在无matlab的电脑上直接运行(Face recognition, can be built from the database, and the statement converted to exe, can be directly shipped without MATLAB computer)
dingwei
- 实现了人脸定位功能，并在yaleB数据库上得到了测试(To achieve the face positioning function, and in the yaleB database has been tested)
FaceLogin
- 基于百度大脑的人脸识别，需要在线申请百度开发者控制台。数据库很简单，用户名和人脸图片，可以自己建(Face recognition based on the Baidu brain, Baidu need online application developer console. The database is very simple, user name and face images, can build their own)
mysql-connector-java-5.1.26-bin
- java eclipse与数据库链接包，语言要一直，面对新手，谢谢(Java eclipse and database link package, the language must always face the novice, thank you)
人脸识别
- 基于ssm框架搭建的，前端通过获取video标签?调用本地的摄像头(获取用户媒体对象,流媒体数据base64)，将流媒体数据画到convas画布上去?,后台调用百度API人脸识别接口，进入百度大脑搜索人脸识别即可获取官网的Secret Key，将前端获取的人脸信息的base64信息和你本地数据库里的人脸信息传到百度人脸识别的接口进行人脸比对，返回一个json数据，result参数 带别人脸相似度, result可自己定义，从而实现人脸识别登录(Based on the SSM framework
stasm
- 人脸识别库，VC2010下速度很快，但是我用C#封装后速度下降，也请大拿能封装个速度快的C#接口，程序也包括linux环境。(Face recognition database, VC2010 is very fast, but I used the falling speed of C# package, please take a fast C# interface package, the program also includes linux.)
人脸识别
- 本程序用到了opencv 中的扩展库opencv contrib, 先用take.cpp来获取自己的数据库，然后在用tria.cpp来训练能检测自己的脸的检测器，再运行recon.cpp来进行人脸检测。(This program uses the extension library opencv contrib in OpenCV. First, take.cpp is used to get its own database, then tria.cpp is used to train th
test_face_photo
- 能够采集人脸并且对照数据库识别进行登录，本程序采用纯jdbc+servlet实现，有大牛觉得哪不对的，请指出，好让我这菜鸟学习学习。(It can collect face and register with database recognition. This program is implemented by pure jdbc+servlet. There is something wrong with Daniel. Please point out, so that I can lea
最近邻分类器LBP
- 局部二值模式LBP+KNN分类方法人脸识别源代码,，内涵数据库，可运行(Local two value pattern LBP+KNN classification method, face recognition source code, connotation database, can be run)
haowenzhang
- 智能家居是一个PC端的产品展示网站，主要是面对社会中高端生活质量较高的人群。主要负责实现 注册页面、登录页面、页面切换以及详情页的渲染等业务的要求。 项目技术： 登入注册页面主要用到的是正则表达式判断格式以及Ajax的异步请求数据 运用HTML+CSS进行简单布局，运用原生Js+JQuery进行渲染。 后台管理界面运用了BootStrap框架,服务器使用Node.js 进行架设, 使用了Express框架进行开发, 数据库使用到了Mongodb。(Smart home is a PC
7，ATKFREC(人脸识别库)
- STM32单片机开发例程中的人脸识别库，可调用(Face Recognition Database)
ATKFREC(人脸识别库)
- 人脸识别库，源自正点原子RT1052开发板附赠资料(Face Recognition Database)