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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Using Visual Rhythms for Detecting Video-Based Facial Spoof Attacks

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Autor(es):
Pinto, Allan [1] ; Schwartz, William Robson [2] ; Pedrini, Helio [1] ; Rocha, Anderson de Rezende [1]
Número total de Autores: 4
Afiliação do(s) autor(es):
[1] Univ Estadual Campinas, Inst Comp, BR-13083970 Campinas - Brazil
[2] Univ Fed Minas Gerais, Dept Comp Sci, BR-31270901 Belo Horizonte, MG - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: IEEE Transactions on Information Forensics and Security; v. 10, n. 5, p. 1025-1038, MAY 2015.
Citações Web of Science: 27
Resumo

Spoofing attacks or impersonation can be easily accomplished in a facial biometric system wherein users without access privileges attempt to authenticate themselves as valid users, in which an impostor needs only a photograph or a video with facial information of a legitimate user. Even with recent advances in biometrics, information forensics and security, vulnerability of facial biometric systems against spoofing attacks is still an open problem. Even though several methods have been proposed for photo-based spoofing attack detection, attacks performed with videos have been vastly overlooked, which hinders the use of the facial biometric systems in modern applications. In this paper, we present an algorithm for video-based spoofing attack detection through the analysis of global information which is invariant to content, since we discard video contents and analyze content-independent noise signatures present in the video related to the unique acquisition processes. Our approach takes advantage of noise signatures generated by the recaptured video to distinguish between fake and valid access videos. For that, we use the Fourier spectrum followed by the computation of video visual rhythms and the extraction of different characterization methods. For evaluation, we consider the novel unicamp video-attack database, which comprises 17 076 videos composed of real access and spoofing attack videos. In addition, we evaluate the proposed method using the replay-attack database, which contains photo-based and video-based face spoofing attacks. (AU)

Processo FAPESP: 11/22749-8 - Desafios em visualização exploratória de dados multidimensionais: novos paradigmas, escalabilidade e aplicações
Beneficiário:Luis Gustavo Nonato
Linha de fomento: Auxílio à Pesquisa - Temático
Processo FAPESP: 10/05647-4 - Computação forense e criminalística de documentos: coleta, organização, classificação e análise de evidências
Beneficiário:Anderson de Rezende Rocha
Linha de fomento: Auxílio à Pesquisa - Apoio a Jovens Pesquisadores