Blogs by OpexAI

September 1 , 2018

Facial Recognition Applications

By Opex AI Team | September 1, 2018
A facial recognition system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source. There are multiple methods in which facial recognition systems work, but in general, they work by comparing selected facial features from given image with faces within a database.
Facial recognition systems are also becoming popular in commercial applications, such as payment authentication and the monitoring of commercial fishing vessels to prevent illegal fishing.
One of the most widely used libraries to help detection and matching, motion estimation and tracking, is OpenCV (Open Source Computer Vision Library). OpenCV is a free, cross-platform library of programming functions aimed at real-time computer vision with several built-in pretrained classifiers for face, eye and smile detection, among others.
Have you noticed that Facebook has developed an uncanny ability to recognize your friends in your photographs? In the old days, Facebook used to make you to tag your friends in photos by clicking on them and typing in their name. Now as soon as you upload a photo, Facebook tags everyone for you .This technology is called face recognition. Facebook’s algorithms are able to recognize your friends’ faces after they have been tagged only a few times. It’s pretty amazing technology — Facebook can recognize faces with 98% accuracy which is pretty much as good as humans can do!
Facial recognition technology has been traditionally associated with the security sector but today there is active expansion into other industries including retail, marketing and health. Occasionally, facial recognition technology may not be able to distinguish between a human face and a photograph. As a result, this flaw can greatly compromise security efforts. In an effort to address this challenge, Trueface.AI, the developers of a facial recognition doorbell called Chui, are using deep learning and facial recognition technology to distinguish a human face from a photograph.
The more cameras populate our normal environments, the more likely big data companies will draw on them for data – to identify not just how many people walk by an advertisement, for example, but who those individuals are. Companies can identify how often someone comes to a physical storefront, even if they pay in cash. Video data becomes actionable in new and increasingly personal ways.