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Books > Computing & IT > Applications of computing > Image processing
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Multi-Modal Face Presentation Attack Detection (Paperback)
Loot Price: R1,010
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Multi-Modal Face Presentation Attack Detection (Paperback)
Series: Synthesis Lectures on Computer Vision
Expected to ship within 10 - 15 working days
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For the last ten years, face biometric research has been
intensively studied by the computer vision community. Face
recognition systems have been used in mobile, banking, and
surveillance systems. For face recognition systems, face spoofing
attack detection is a crucial stage that could cause severe
security issues in government sectors. Although effective methods
for face presentation attack detection have been proposed so far,
the problem is still unsolved due to the difficulty in the design
of features and methods that can work for new spoofing attacks. In
addition, existing datasets for studying the problem are relatively
small which hinders the progress in this relevant domain. In order
to attract researchers to this important field and push the
boundaries of the state of the art on face anti-spoofing detection,
we organized the Face Spoofing Attack Workshop and Competition at
CVPR 2019, an event part of the ChaLearn Looking at People Series.
As part of this event, we released the largest multi-modal face
anti-spoofing dataset so far, the CASIA-SURF benchmark. The
workshop reunited many researchers from around the world and the
challenge attracted more than 300 teams. Some of the novel
methodologies proposed in the context of the challenge achieved
state-of-the-art performance. In this manuscript, we provide a
comprehensive review on face anti-spoofing techniques presented in
this joint event and point out directions for future research on
the face anti-spoofing field.
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