Face Liveness Detection

G. Kiran Kumar, N. Rithik Reddy, K. Anudeepika, T. Abhishek


Face recognition systems are becoming more prevalent than ever. From face recognition on your iPhone/smartphone, to face recognition for mass surveillance, face recognition systems are being utilized everywhere. However, face recognition systems are easily fooled by “spoofing” and “non-real” faces. Face recognition systems can be circumvented simply by holding up a photo of a person (whether printed, on a smartphone, etc.) to the face recognition camera. In order to make face recognition systems more secure, we need to be able to detect such fake/non-real faces — liveness detection is the term used to refer to such algorithms. In order to create the liveness detector, we’ll be training a deep neural network capable of distinguishing between real versus fake faces and then create a Python + OpenCV script capable of taking our trained liveness detector model and apply it to real-time video.

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Copyright (c) 2020 G. Kiran Kumar, N. Rithik Reddy, K. Anudeepika, T. Abhishek

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