Presentation Attack Detection in Face Recognition System
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One of the quickest, most precise and easily available biometric recognition system is Face recognition. These systems have wide range of uses like phone verification, payment method security checks, border control and surveillance. These systems however, are subject to a variety of spoof attacks which are also known as presentation attacks. Hence it is necessary that efficient face anti-spoofing methods are developed. Here in our research work, we use CNN (convolutional neural network) model along with class activation maps for detection of spoof attacks. This approach helps us extract local information and CNN aids in the development of a robust model. We have performed experiments on challenging benchmark dataset OULU-NPU. We use Class Activation Map for the classification task. We achieved an accuracy of 95% using the proposed approach.
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