Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/86577
Type: Artigo de periódico
Title: Face Liveness Detection Using Dynamic Texture
Author: Pereira T.D.F.
Komulainen J.
Anjos A.
De Martino J.M.
Hadid A.
Pietikainen M.
Marcel S.
Abstract: User authentication is an important step to protect information, and in this context, face biometrics is potentially advantageous. Face biometrics is natural, intuitive, easy to use, and less human-invasive. Unfortunately, recent work has revealed that face biometrics is vulnerable to spoofing attacks using cheap low-tech equipment. This paper introduces a novel and appealing approach to detect face spoofing using the spatiotemporal (dynamic texture) extensions of the highly popular local binary pattern operator. The key idea of the approach is to learn and detect the structure and the dynamics of the facial micro-textures that characterise real faces but not fake ones. We evaluated the approach with two publicly available databases (Replay-Attack Database and CASIA Face Anti-Spoofing Database). The results show that our approach performs better than state-of-the-art techniques following the provided evaluation protocols of each database. © 2014 Pereira et al.; licensee Springer.
Editor: Hindawi Publishing Corporation
Rights: aberto
Identifier DOI: 10.1186/1687-5281-2014-2
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-84901975380&partnerID=40&md5=ac51eb957384f22b4c3a88da86508597
Date Issue: 2014
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
2-s2.0-84901975380.pdf2.24 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.