MIT 人脸数据库 由麻省理工大学媒体实验室创建,包含16位志愿者的2,592张不同姿态, 光照和大小的面部图像。 其他人脸数据库也有上传 比如： Yale人脸库（美国）CMU-PIE人脸数据库Yale 人脸数据库B MIT 人脸数据库 ORL人脸库（英国） INRIA数据库 UMIST人脸库（英国）KinFace人脸数据库 AR人脸库（美国）Bern人脸库

史上最全的人脸库，自己毕业设计时做人脸识别时收集的，包括ORL人脸库、Yale人脸库、FERET人脸库及MIT人脸库。ORL人脸库中包括92*112的bmp格式及pgm格式的各400幅人脸；Yale人脸库中包括100*100的bmp格式的15个人的人脸，每个人11幅图像；MIT人脸库中包括人脸20*20的bmp格式2706幅图及非人脸20*20的bmp格式4381幅图，FERET人脸库包括80*80的1600幅图像。如此全面，做人脸识别比不可少的数据库，绝对值得下载。

MIT人脸库 训练，测试用的人脸图像 opencv训练分类器可以用到 还有别的库可是太大了。。。

做人脸识别的标准人脸库，包含人脸和非人脸2部分。

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."

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."

由麻省理工大学媒体实验室创建,包含16位志愿者的2,592张不同姿态,光照和大小的面部图像.

MIT人脸数据库，多角度人脸，并且归一化到19*19，适合做人脸识别检测

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."

MIT人脸图像库,包括人脸样本和非人脸样本，已经切割好的，可以直接用来训练