基于MATLAB的人脸眼睛嘴巴检测,内涵说明书,摘要,代码等,同时含有自制神经网络训练集的代码(用户运行代码做出表情代码自动归类训练集合),主代码通过先检测脸部特征,后综合检测眼睛张开关闭+嘴巴张开关闭判定人脸是否处在疲劳状态,代码本人已经调试运行无误。
2019-12-21 22:08:52 6.85MB matla 人脸识 眼睛识 嘴巴识
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lfw_face数据集_193M(百度云链接) lfw_face数据集_193M(百度云链接) lfw_face数据集_193M(百度云链接)
2019-12-21 22:02:43 64B lfw_数据集
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seetaface人脸识别windows java实现
2019-12-21 21:58:21 268KB face
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使用的是opencv3.4.1版本。face_recognition可以使用apt-get install 安装,这也是为什么用ubuntu的原因。有问题欢迎留言讨论。
2019-12-21 21:54:55 897KB opencv face_recogni 人脸对比
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博客地址:https://blog.csdn.net/wen_fei/article/details/80261047 人脸识别源代码,包括使用opencv、dlib和cnn实现的人脸检测、opencv实现的人脸对齐以及vgg-face的人脸特征提取等,最后余弦函数计算相似度,并提供flask部署代码,可以放在服务器上远程调用
2019-12-21 21:53:27 9KB 人脸识别源码
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《About Face 4: 交互设计精髓》是《About Face 3:交互设计精髓》的升级版,此次升级把全书的结构重组优化,更加精练和易用;更新了一些适合当下时代的术语和实例,文字全部重新编译,更加清晰易读;增加了更多目标导向设计过程的细节,更新了现行实践,重点增加 移动和触屏平台交互设计,其实《About Face 4: 交互设计精髓》多数内容适用于多种平台。 《About Face 4: 交互设计精髓》是一本数字产品和系统的交互设计指南,全面系统地讲述了交互设计的过程、原理和方法,涉及的产品和系统有个人计算机上的个人和商务软件、Web 应用、手持设备、信息亭、数字医疗系统、数字工业系统等。运用《About Face 4: 交互设计精髓》的交互设计过程和方法,有助于了解使用者和产品之间的交互行为,进而更好地设计出更具吸引力和更具市场竞争力的产...
2019-12-21 21:51:52 147.37MB 设计
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原版的Yale人脸库(格式转换了一下),15个人,每人11张图片,灰度,png格式,100x100,有表情、光照和眼镜变化,已剪裁和对齐
2019-12-21 21:32:27 1.47MB Yale 人脸库 face png
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The CAS-PEAL face database has been constructed under the sponsors of National Hi-Tech Program and ISVISION by the Face Recognition Group of JDL, ICT, CAS. The goals to create the PEAL face database include: providing the worldwide researchers of FR community a large-scale Chinese face database for training and evaluating their algorithms; facilitating the development of FR by providing large-scale face images with different sources of variations, especially Pose, Expression, Accessories, and Lighting (PEAL); advancing the state-of-the-art face recognition technologies aiming at practical applications especially for the oriental. Currently, the CAS-PEAL face database contains 99,594 images of 1040 individuals (595 males and 445 females) with varying Pose, Expression, Accessory, and Lighting (PEAL). For each subject, 9 cameras spaced equally in a horizontal semicircular shelf are setup to simultaneously capture images across different poses in one shot. Each subject is also asked to look up and down to capture 18 images in another two shots. We also considered 5 kinds of expressions, 6 kinds accessories (3 glasses, and 3 caps), and 15 lighting directions. This face database is now partly made available (a subset named by CAS-PEAL-R1, contain 30,900 images of 1040 subjects) for research purpose only on a case-by-case basis only. JDL is serving as the technical agent for distribution of the database and reserves the copyright of all the images in the database.
2019-12-21 21:32:12 37B 中国人脸 数据集  dataset deeplearning
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CMU Multi-PIE人脸数据库包含超过750,000张337人的图像,这些图像在五个月内最多可​​记录四次。受试者在15个视点和19个照明条件下成像,同时显示一系列面部表情。此外,还获得了高分辨率正面图像。总的来说,数据库包含超过305GB的面部数据。 资源包括PIE照明子集(1154张人脸灰度图,32*32)和三个Pose05、Pose07、Pose09子集(分别包括3332张、1629张、859张人脸灰度图,64*64)。
2019-12-21 21:29:12 14.38MB 人脸数据集 人脸表情识别
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这是用matlab语言编写的一段代码,可以在一幅图片上将人脸检测出来,并用矩形框框起来,然后裁剪下来,另存为图片。
2019-12-21 21:25:54 649B face detection
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