Due to the various factors like illumination, expression, and pose variation etc., human face seem different in multiple
occasions. To determine the efficiency of the different face recognition algorithms, it requires benchmark face images.
This paper presents a comprehensive study of the available 2D face databases and also introduces the creation of a visual
face database, North-East Indian (NEI) Face Database, which is under development in the Biometrics Laboratory of
Tripura University, India. It contains high quality face images of 292 individuals of different tribe and non-tribe people
of Mongolian origin collected from the North-Eastern states of India. The database contains four different types of
illumination variations, eight different expressions, faces wearing glasses and each of these variations are being clicked
concurrently from five different angles to provide pose variation using five CMOS sensor cameras, in a controlled indoor
environment. Three different resolutions are being used for capturing the database images. Some baseline face
recognition algorithms have also been tested using the Support Vector Machines (SVM) classifier on the NEI face
database, which may be used as the control algorithm performance score by other researchers.