Face Anti-Spoofing methods for face recognition in Python

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I am working on a face recognition project where a I can first enroll myself and then start a recognize script which will start my webcam and it will recognize myself. I am following this article and its working perfectly fine.

What I have noticed is that if I show my photo to the camera instead myself in front of the camera, it still detects and recognize my face. There is no anti-spoofing involved in it. I want to include anti-spoofing method in the code so that it can detect weather the face detected/recognized is real of fake. For this I thought of following below approaches:

1. Eye blink detection: Initially I thought I would implement an eye blink detection algorithm, but it also has its disadvantage. What if a real face person didnt blinked his eyes for sometime, in that case our code will tag that face as fake. Also the eyes was also not getting detected at a distance of 1-1.5meter from the camera.

2. Using temperature sensor: I also interfaced omron thermal sensor so that I can get the temperature of the face. In normal human face, temperature is always above a threshold. In case of face in photo, it will always be below that threshold. I implemented this and it was working fine. But later realized that if someone showed photo in phone, in that case due to phone's high screen temperature, its always more than the threshold and thus it is tagged in as real photo.

Above mentioned methods didn't worked for me. I am looking for a simple solution which can work in all the scenarios. I am doing this project on raspberry pi, so looking for a solution which is compatible with raspberry pi. Please help. Thanks

face-recognition python
3 Answers

Sorry for any mistake because I am not from raspberry pi's background but as a decent guy helping people I think that you should try resolution check (if it is possible) because phone's screen would always have less resolution than the real face. And then you can use it with the eye blink method to catch hold of a phone as photos do not blink eyes. Average human blinks 12 times in a minute so 1 time every 5 seconds . This will help you to catch hold of the printed photos. Hope this would help.

user_140525540

You should use an object detector on top of the face detector. It can definitely detect a phone.
You could retrain it to detect a photo being held up as well.

Have the object detector run first, save the bounding box coordinates of the phone, then see if the face bounding box coordinates reside inside of the phone.

user_101887190

I'm working on a face recognition system right now as my thesis project. Have you tried this article? Adrian says that it is usable in Raspberry Pi, but it means we have to install TensorFlow & Keras to do it. I think this could help.

user_129298740
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