TY - GEN
T1 - Face liveness detection using variable focusing
AU - Kim, Sooyeon
AU - Yu, Sunjin
AU - Kim, Kwangtaek
AU - Ban, Yuseok
AU - Lee, Sangyoun
PY - 2013
Y1 - 2013
N2 - As Face Recognition(FR) technology becomes more mature and commercially available in the market, many different anti-spoofing techniques have been recently developed to enhance the security, reliability, and effectiveness of FR systems. As a part of anti-spoofing techniques, face liveness detection plays an important role to make FR systems be more secured from various attacks. In this paper, we propose a novel method for face liveness detection by using focus, which is one of camera functions. In order to identify fake faces (e.g. 2D pictures), our approach utilizes the variation of pixel values by focusing between two images sequentially taken in different focuses. The experimental result shows that our focus-based approach is a new method that can significantly increase the level of difficulty of spoof attacks, which is a way to improve the security of FR systems. The performance is evaluated and the proposed method achieves 100% fake detection in a given DoF(Depth of Field).
AB - As Face Recognition(FR) technology becomes more mature and commercially available in the market, many different anti-spoofing techniques have been recently developed to enhance the security, reliability, and effectiveness of FR systems. As a part of anti-spoofing techniques, face liveness detection plays an important role to make FR systems be more secured from various attacks. In this paper, we propose a novel method for face liveness detection by using focus, which is one of camera functions. In order to identify fake faces (e.g. 2D pictures), our approach utilizes the variation of pixel values by focusing between two images sequentially taken in different focuses. The experimental result shows that our focus-based approach is a new method that can significantly increase the level of difficulty of spoof attacks, which is a way to improve the security of FR systems. The performance is evaluated and the proposed method achieves 100% fake detection in a given DoF(Depth of Field).
UR - http://www.scopus.com/inward/record.url?scp=84887493880&partnerID=8YFLogxK
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U2 - 10.1109/ICB.2013.6613002
DO - 10.1109/ICB.2013.6613002
M3 - Conference contribution
AN - SCOPUS:84887493880
SN - 9781479903108
T3 - Proceedings - 2013 International Conference on Biometrics, ICB 2013
BT - Proceedings - 2013 International Conference on Biometrics, ICB 2013
PB - IEEE Computer Society
T2 - 6th IAPR International Conference on Biometrics, ICB 2013
Y2 - 4 June 2013 through 7 June 2013
ER -