|Illumination invariant face recognition using near-infrared images|
|Li, Stan Z.; Chu, RuFeng; Liao, ShengCai; Zhang, Lun
|Source Publication||IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
|Abstract||Most current face recognition systems are designed for indoor, cooperative-user applications. However, even in thus constrained applications, most existing systems, academic and commercial, are compromised in accuracy by changes in environmental illumination. In this paper, we present a novel solution for illumination invariant face recognition for indoor, cooperative-user applications. First, we present an active near infrared (NIR) imaging system that is able to produce face images of good condition regardless of visible lights in the environment. Second, we show that the resulting face images encode intrinsic information of the face, subject only to a monotonic transform in the gray tone; based on this, we use local binary pattern (LBP) features to compensate for the monotonic transform, thus deriving an illumination invariant face representation. Then, we present methods for face recognition using NIR images; statistical learning algorithms are used to extract most discriminative features from a large pool of invariant LBP features and construct a highly accurate face matching engine. Finally, we present a system that is able to achieve accurate and fast face recognition in practice, in which a method is provided to deal with specular reflections of active NIR lights on eyeglasses, a critical issue in active NIR image-based face recognition. Extensive, comparative results are provided to evaluate the imaging hardware, the face and eye detection algorithms, and the face recognition algorithms and systems, with respect to various factors, including illumination, eyeglasses, time lapse, and ethnic groups.|
Near Infrared (Nir)
Local Binary Pattern (Lbp)
|WOS Headings||Science & Technology
|WOS Research Area||Computer Science
|WOS Subject||Computer Science, Artificial Intelligence
; Engineering, Electrical & Electronic
|Affiliation||1.Chinese Acad Sci, Inst Automat, Ctr Biometr & Secur Records, Beijing 100080, Peoples R China|
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China
Li, Stan Z.,Chu, RuFeng,Liao, ShengCai,et al. Illumination invariant face recognition using near-infrared images[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2007,29(4):627-639.
Li, Stan Z.,Chu, RuFeng,Liao, ShengCai,&Zhang, Lun.(2007).Illumination invariant face recognition using near-infrared images.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,29(4),627-639.
Li, Stan Z.,et al."Illumination invariant face recognition using near-infrared images".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 29.4(2007):627-639.
|Files in This Item:||
||There are no files associated with this item.
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.