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Security evaluation and implementation of facial recognition algorithms

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dc.contributor.author Dwivedi, Purusharth
dc.contributor.author Chang, Donghoon (Advisor)
dc.date.accessioned 2018-09-25T09:25:13Z
dc.date.available 2018-09-25T09:25:13Z
dc.date.issued 2017-11-17
dc.identifier.uri http://repository.iiitd.edu.in/xmlui/handle/123456789/688
dc.description.abstract The following report discusses various facial recognition spoofing techniques in use today, and compares various algorithms, that have been developed for detecting the same. Continuing towards the previous semester’s goal of developing a robust facial facial recognition system, an anti-spoofing module becomes a necessity as it plays a very important role of differentiating between genuine face and fake faces. Even the most advanced algorithms today, such as the FaceNet are prone to spoofing attacks, like the warped photo attack, cut-photo attack etc. Further, various deep-learning based architectures have been implemented and their performance on the task of detecting spoofed images compared. en_US
dc.language.iso en_US en_US
dc.publisher IIIT-Delhi en_US
dc.subject Computer vision en_US
dc.subject Facial recognition en_US
dc.subject False acceptance rate (FAR) en_US
dc.subject False rejection rate (FRR) en_US
dc.subject Algorithms en_US
dc.subject Image Analysis en_US
dc.subject Machine learning en_US
dc.subject K-nearest neighbours (KNN) en_US
dc.subject Histograms of oriented gradients( HOG) en_US
dc.subject Local binary patterns (LBP) en_US
dc.subject Eigenface en_US
dc.subject Principal component analysis (PCA) en_US
dc.subject Support vector machines (SVM) en_US
dc.subject Principal components analysis(PCA) en_US
dc.title Security evaluation and implementation of facial recognition algorithms en_US
dc.type Other en_US

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