cơ sở dữ liệu cho nhận dạng mặt người

[Ngocnamtq]

Chào mọi người !
hiện mình đang làm về nhận dạng mặt người vì vậy mình rất cần data nguồn để test nếu ai có thì có thể cho mình xin.

[vagabondtt]

- Download face database CBCL SOFTWARE
- Source: Tutorial: OpenCV haartraining (Rapid Object Detection With A Cascade of Boosted Classifiers Based on Haar-like Features) - Naotoshi Seo

[lethang85]

Xem ở đây nhé

Face Recognition with OpenCV — OpenCV 2.4.7.0 documentation

Let’s get some data to experiment with first. I don’t want to do a toy example here. We are doing face recognition, so you’ll need some face images! You can either create your own dataset or start with one of the available face databases, Face Recognition Homepage - Databases gives you an up-to-date overview. Three interesting databases are (parts of the description are quoted from http://face-rec.org):

• AT&T Facedatabase The AT&T Facedatabase, sometimes also referred to as ORL Database of Faces, contains ten different images of each of 40 distinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no glasses). All the images were taken against a dark homogeneous background with the subjects in an upright, frontal position (with tolerance for some side movement).
• Yale Facedatabase A, also known as Yalefaces. The AT&T Facedatabase is good for initial tests, but it’s a fairly easy database. The Eigenfaces method already has a 97% recognition rate on it, so you won’t see any great improvements with other algorithms. The Yale Facedatabase A (also known as Yalefaces) is a more appropriate dataset for initial experiments, because the recognition problem is harder. The database consists of 15 people (14 male, 1 female) each with 11 grayscale images sized pixel. There are changes in the light conditions (center light, left light, right light), facial expressions (happy, normal, sad, sleepy, surprised, wink) and glasses (glasses, no-glasses).
  The original images are not cropped and aligned. Please look into the Appendix for a Python script, that does the job for you.
• Extended Yale Facedatabase B The Extended Yale Facedatabase B contains 2414 images of 38 different people in its cropped version. The focus of this database is set on extracting features that are robust to illumination, the images have almost no variation in emotion/occlusion/... . I personally think, that this dataset is too large for the experiments I perform in this document. You better use the AT&T Facedatabase for intial testing. A first version of the Yale Facedatabase B was used in [BHK97] to see how the Eigenfaces and Fisherfaces method perform under heavy illumination changes. [Lee05] used the same setup to take 16128 images of 28 people. The Extended Yale Facedatabase B is the merge of the two databases, which is now known as Extended Yalefacedatabase B.