Face recognition in unconstrained situations continues to be a challenging research domain. This paper have presented an extensive survey of face databases for constrained and unconstrained environments. It focuses mostly on novel databases that are freely available for the research purposes. Most of the popular face databases are concisely introduced and compared. The purpose of this review paper is to assist the young budding researchers in the area of face recognition by compiling the most widely used face databases and the link to download them so as to motivate their further research.

The image size, image type and the other specifications describes about the complexity of face database which in turn shows the robustness of different algorithms of face recognition. The different face databases are created to evaluate the effect of changes on the several types of conditions of an image. AR Faces, FERET, CMU-PIE, Asian and Indian face database are the most widely used 2D face image databases. Each database provides a platform to access the particular challenges of uncontrolled conditions. For example, CMU-PIE is used for more illumination and poses changes. FERET gives a good testing platform for large probe and gallery sets. AR Faces gives the natural occluded face images. Asian face database consists of 2D face images of female and male with pose, illumination, expression occlusion and expressions. The Indian face database comprises of face images with variation in expression and poses.