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Future of Facial Recognition Technology

Facial Recognition Technology

ICT | Jun, 2019

Over the years, movies have fixed a futuristic fantasy in our minds that a time will come when software would be used to recognize people by their faces. A time when our faces will be our ID cards. With advent of facial recognition technology, that time is already here.

Today, along with drones, AI and IoT, facial recognition technology is also defining our millennium. Facial recognition is a biometric technology used for authentication and examination of individuals by correlating the facial features from an image with the stored facial database. Face Recognition is one of the most popular applications of image analysis software and no more considered as a subject of science fiction. Earlier, this technology was only used for security and surveillance purposes, but it has safely transitioned to the real world in recent times. Today, companies are pitching facial recognition software as the future of everything from retail to policing.

The Facial Recognition- “Saga”

Woody Bledsoe, Helen Chan Wolf, and Charles Bisson are known to be the pioneers of facial recognition technology. During the 1960s, they worked on recognizing human faces using a computer but only a part of there work was published and recognized since their project was funded by some intelligence agency. Later in the 1970s, Goldstein identified 21 facial measurement points. Later in 1988, Kirby & Sirovich normalized a face image using less than 100 measurement points. Finally, in 1991, first crude facial detection was done by Turk & Pentland. 


Facial Recognition – “The Last Step”

A facial recognition system is used to identify and verify a person from an image or video source. It uses biometric software’s along with AI enabled devices for mapping facial features and brings out the recognition step. A facial recognition software differentiates a face from rest of the background in the image. The software first recognizes the face then measures different facial features. The software recognizes these features as nodal points. A human face consists of 80 nodal points. After measuring these features a numerical code for the same is created and stored in the database. This is known as the faceprint.

Earlier the software relied on 2D image to identify or verify another 2D image from the database but today it uses a 3D model for the same. This 3D model is more reliable, better, effective and accurate than its 2D counterpart. Using the 3D software, the system goes through a series of steps, facial recognition forming the last one.

Face detection is the first step of process wherein face is detected from an image or a video. Once a face is detected, the system identifies its size and position. In the next step, a faceprint is generated by measuring the facial features. Finally, using the principle of object classification, the actual process of matching data features to the details of individuals already stored in database is done and facial recognition process is complete.