The CAS-PEAL large-scale Chinese face database and baseline evaluations
The CAS-PEAL large-scale Chinese face database and baseline evaluations
复制标题
CAS-PEAL大规模华人人脸数据库及基线评估
DOI：
10.1109/tsmca.2007.909557
复制
发表时间：
2008-01-01
影响因子：
--
通讯作者：
Zhao, Debin
中科院分区：
文献类型：
--
作者：
Gao, Wen;Cao, Bo;Zhao, Debin
本文介绍了一个大型的中国人脸数据库CAS-PEAL人脸数据库的获取和内容。建立CAS-PEAL人脸数据库的目标包括：1）在一个统一的数据库中为世界各地的人脸识别研究人员提供不同的变化来源，特别是姿势，表情，附件和照明（PEAL），以及详尽的地面实况信息; 2）通过使用离线人脸识别技术，推进面向实际应用的最新人脸识别技术。货架成像设备和设计正常的人脸变化的数据库; 3）提供了一个大规模的蒙古人人脸数据库。目前，CAS-PEAL人脸数据库包含1040个人（595名男性和445名女性）的99594张图像。总共有九个摄像头水平安装在弧形臂上，以同时捕捉不同姿势的图像。每个受试者被要求直视前方，向上和向下，在三个镜头中获得27个图像。数据库中还包括五种面部表情，六种配件和15种灯光变化。数据库的一个选定的子集（CAS-PEAL-RI，包含1040名受试者的30863张图像）现在可供其他研究人员使用。我们讨论了基于CAS-PEAL-R1数据库的评估协议，并提出了四种算法的性能作为基线做以下工作：1）初步评估数据库的人脸识别算法的难度; 2）使用数据库的研究人员的偏好评估结果; 3）确定常用算法的优点和缺点。
In this paper, we describe the acquisition and contents of a large-scale Chinese face database: the CAS-PEAL face database. The goals of creating the CAS-PEAL face database include the following: 1) providing the worldwide researchers of face recognition with different sources of variations, particularly pose, expression, accessories, and lighting (PEAL), and exhaustive ground-truth information in one uniform database; 2) advancing the state-of-the-art face recognition technologies aiming at practical applications by using off-the-shelf imaging equipment and by designing normal face variations in the database; and 3) providing a large-scale face database of Mongolian. Currently, the CAS-PEAL face database contains 99594 images of 1040 individuals (595 males and 445 females). A total of nine cameras are mounted horizontally on an arc arm to simultaneously capture images across different poses. Each subject is asked to look straight ahead, up, and down to obtain 27 images in three shots. Five facial expressions, six accessories, and 15 lighting changes are also included in the database. A selected subset of the database (CAS-PEAL-RI, containing 30863 images of the 1040 subjects) is available to other researchers now. We discuss the evaluation protocol based on the CAS-PEAL-R1 database and present the performance of four algorithms as a baseline to do the following: 1) elementarily assess the difficulty of the database for face recognition algorithms; 2) preference evaluation results for researchers using the database; and 3) identify the strengths and weaknesses of the commonly used algorithms.