A New Multispectral Method for Face Liveness Detection

A face recognition system can be deceived by photos, mimic masks, mannequins and etc. And with the advances in the 3D printing technology, a more robust face liveness detection method is needed. In this paper, a gradient-based multispectral method has been proposed for face liveness detection. Based...

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Bibliographic Details
Published in:Proceedings - IEEE Computer Society Conference on Pattern Recognition and Image Processing pp. 922 - 926
Main Authors: Yueyang Wang, Xiaoli Hao, Yali Hou, Changqing Guo
Format: Conference Proceeding
Language:English
Published: IEEE 01.11.2013
Subjects:
Cameras
Face
Face liveness detection
Feature extraction
Hair
Lighting
multispectral imaging
reflectance
Reflectivity
Skin
ISSN:0730-6512
Online Access:Get full text
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Summary:A face recognition system can be deceived by photos, mimic masks, mannequins and etc. And with the advances in the 3D printing technology, a more robust face liveness detection method is needed. In this paper, a gradient-based multispectral method has been proposed for face liveness detection. Based on two spectral bands, the developed method is tested for the classification of genuine faces and common disguised faces. A true positive rate of 96.7% and a true negative rate of 97% have been achieved. The performance of the method is also tested when face rotation occurs. The contributions of this paper are: First, a gradient-based multispectral method has been proposed. Except for the reflectance of the skin regions, the reflectance of other distinctive regions in a face are also considered in the developed method. Second, the method is tested based on a dataset with both planar photos and 3D mannequins and masks. The performance on different face orientations is also discussed.
ISSN:0730-6512
DOI:10.1109/ACPR.2013.169