Highlight: In this post you are going to learn how to detect facial landmarks in an image using dlib and OpenCV. This knowledge will be useful, since facial landmarks are the key features in a large number of facial analysis methods and algorithms. Face recognition, face alignment, facial expression recognition, face swapping, drowsiness detection, blink detection, head pose estimation, are the few examples in which facial landmarks play a fundamental role. Face Swapping pictures are the extremely popular trend on social media. Snapchat, Cupace, MSQRD are probably the most widely used apps having the face swapping option.

In 1993, Peter Steiner published a cartoon in The New Yorker with the caption, "On the Internet, nobody knows you're a dog." It grew to be an internet meme and captured many of the benefits – and drawbacks – of internet anonymity. The benefits include internet businesses not being capable of discriminating against individuals the same way brick-and-mortar might. There can be more freedom to express diverging opinions. The downsides, of course, are becoming more apparent every day: the rise of fake news, disinformation, and the ability for people to say things they really ought not to say, with impunity.

A facial recognition system can identify someone even if their face is covered up. The Disguised Face Identification (DFI) system uses an AI network to map facial points and reveal the identity of people. It could eventually help to pick out criminals, protesters, or anyone who hides their identity by covering themselves with masks, scarves or sunglasses. The software could also see the end of public anonymity, sparking privacy concerns from one academic, who has labelled it'authoritarian'. A facial recognition system can identify someone even if their face is covered up.