Face detection, recognition and tracking are revolutionary technologies that have been deployed on mobile phones, webcams, and digital cameras. With the help of this advancement in technology, we are now able to detect human faces and recognize any specific person in a crowd.
This is a really superb and game changer innovation that has taken the technology world by storm. Now it’s only a matter of time for face detection technology to be deployed across different web applications in different sectors.
In digital cameras, face detection technology is used for the purpose of autofocus; in webcams, it is used to take an instant passport-sized photograph of you; and in mobile phones, it is one measure used for the authentication of its user.
The future of face detection and recognition technology is very promising. This is because it is successfully used by the police and other law enforcement agencies to detect and fight crime in many countries of the world.
clmtrackr is also an open source face detection library like the ones I’ve mentioned above. You can download it from GitHub for free.
It makes use of Constrained Local Models to precisely identify and track the facial features. It then returns an array, which contains all the coordinates of a face model.
The interesting thing about clmtrackr is that it is capable of face swapping and masking. It really forms an all-in-one package.
In its GitHub repository, you will find 3 major folders e.g. “img”, “cam” and “wasm”. All of these folders contain basic demo of how this library works. Its “img” folder has an example which clearly demonstrates how you can detect a human face in images. The “cam” folder contains a demo which shows the tracking of face in real-time. Basically “wasm” folder is there to provide an example about how you can compile pico.js to WebAssembly.
jQuery Face Detection Plugin
jQuery Face Detection Plugin helps to detect different human faces inside an image, canvas or video. It makes use of an advanced algorithm to get an array of all the objects found in a face. These objects include coordinates, height and width, offset, position, scale and confidence of a face.
The fact that it helps in fighting crime and used for authentication of the real owner of a mobile phone makes it a lot more compelling.
In the nearest future, it will be used on web applications and its usefulness will become irresistible. It may be deployed in schools during examinations to detect and recognize the faces of students who are allowed to appear in exam. It can also be used during the recruitment process. The future is already here. Our lives can only get better and smarter with the passage of time.