CAS-PEAL: A Large-Scale Chinese Face Database and Some Primary Evaluations

As the basis of research, development and evaluation of face recognition algorithms, face image database is of great importance. In this paper, we introduce the construction and basic content of the CAS-PEAL, large-scale Chinese face database and some primary evaluation results based on the database. The CAS-PEAL face database consists of 99 450 facial images of 1 040 Chinese individuals. All the images in the database were collected in specially designed environment with four principal variations of pose, expression, accessory and lighting, as well as three other variations in terms of background, distance and aging. Currently, the standard training set and probe set of CAS-PEAL face database have been made publicly available for research purpose only on a case-by-case basis. Compared with other public face databases, CAS-PEAL excels in its large-scale and variation modes and is expected to have positive impact on the development and evaluation of face recognition algorithms. In addition, as an oriental face image database, CAS-PEAL makes possible the comparison of algorithms' performance between different ethnic groups and will benefit the application of face recognition technology in China. This paper also gives the evaluation results of two basic face recognition algorithms (Eigenface and Correlation) and two commercial systems, explains the difficulty of the database to the face recognition algorithms and analyses the current development status of face recognition technology.