Title :
The CASIA NIR-VIS 2.0 Face Database
Author :
Li, Stan Z. ; Dong Yi ; Zhen Lei ; Shengcai Liao
Author_Institution :
Nat. Lab. of Pattern Recognition, Inst. of Autom., Beijing, China
Abstract :
In recent years, heterogeneous face biometrics has attracted more attentions in the face recognition community. After published in 2009, the HFB database has been applied by tens of research groups and widely used for Near infrared vs. Visible light (NIR-VIS) face recognition. Despite its success the HFB database has two disadvantages: a limited number of subjects, lacking specific evaluation protocols. To address these issues we collected the NIR-VIS 2.0 database. It contains 725 subjects, imaged by VIS and NIR cameras in four recording sessions. Because the 3D modality in the HFB database was less used in the literature, we don´t consider it in the current version. In this paper, we describe the composition of the database, evaluation protocols and present the baseline performance of PCA on the database. Moreover, two interesting tricks, the facial symmetry and heterogeneous component analysis (HCA) are also introduced to improve the performance.
Keywords :
cameras; face recognition; infrared imaging; principal component analysis; visual databases; 3D modality; CASIA NIR-VIS 2.0 face database; HCA; HFB database; NIR camera; NIR-VIS 2.0 database; NIR-VIS face recognition; PCA; VIS camera; database composition; evaluation protocols; face recognition community; facial symmetry; heterogeneous component analysis; heterogeneous face biometrics; near infrared; visible light; Databases; Face; Face recognition; Feature extraction; Principal component analysis; Protocols; Training;
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2013 IEEE Conference on
Conference_Location :
Portland, OR
DOI :
10.1109/CVPRW.2013.59