利用肤色分割进行人脸检测的MATLAB实现程序，容易理解，效果还不错

C++与Opencv人脸检测与识别系统，包含可执行程序以及源代码，可运行和参考学习。

libfacedetection-master，人脸识别库，人脸检测库

数字图像处理大作业 内容 Canny 边缘检测 OTSU 图像分割方法 OpenCV + Python 实现人脸检测

主要介绍了tracking.js实现前端人脸识别功能，本文通过实例代码截图的形式给大家展示的非常详细，对大家的学习或工作具有一定的参考借鉴价值,需要的朋友可以参考下

可运行的人脸识别系统，由于上传文件大小有限，需要用户自己下载OpenCV2.0的几个dll文件，算法部分目前分为4个模块：人脸对齐、光照归一化、特征提取和选择、子空间降维，每个模块是一个项目，每个项目生成一个dll供功能部分隐式调用。

通过matlab自带vision工具箱检测图片中人脸，矩形框框出，并切割出人脸单独保存图片。

这是卡内基梅隆大学的公开人脸测试集。测试集共分四个文件夹，分别为测试集A、B、C和旋转测试集。由于大小限制，因此将四个文件夹分开上传 The image dataset is used by the CMU Face Detection Project and is provided for evaluating algorithms for detecting frontal views of human faces. This particular test set was originally assembled as part of work in Neural Network Based Face Detection. It combines images collected at CMU and MIT. Please give appropriate acknowledgements when you use these test sets. In the lists of files below, you will find references to Test Sets A, B, C and the Rotated Test Set. Test Set B was provided by Kah-Kay Sung and Tomaso Poggio at the AI/CBCL Lab at MIT, and Test Sets A,C and the rotatated test set were collected here at CMU (by Henry A. Rowley, Shumeet Baluja, and Takeo Kanade). In [Schneiderman and Kanade, 2000] and [Schneiderman and Kanade, 1998] we refer to the combination of test sets A, B, and C as the "combined test sets of Sung and Poggio and Rowley, Baluja, and Kanade." In [Rowley, Baluja, and Kanade, 1998] we refer to the combination of sets A, B, C as "test set one" and in [Rowley, Baluja, and Kanade, 1997] we refer to it as the "upright set" as distinguished from the "rotated set."

JS 人脸检测

ESP-WHO是一个基于ESP32的人脸检测和识别平台