Face recognition describes a biometric technology that attempts to establish an individual’s identity. Also known as facial recognition or face detection, the process works using a computer application that captures a digital image of an individual’s face (sometimes taken from a video frame) and compares it to images in a database of stored records. How Facial Recognition Technology Works
Face recognition uses biometrics to verify identity.
Facial recognition systems employ an algorithm that can predict whether there’s a match based on numerous points on an individual’s face. While the human eye is easily fooled by facial hair, hats or other factors, facial recognition technology is far more accurate in seeing matches. This technology is therefore frequently used for security and surveillance purposes (e.g. helping retail stores identify known criminals and airports identify individuals on terrorist watchlists).
While face recognition systems aren’t always100% accurate, they do an excellent job of predicting how likely it is that an individual matches with someone in the database. Accuracy is one of the most important factors in determining a facial recognition system’s success. And therefore, successful facial recognition systems must offer a high degree of accuracy in their predictions. Face Recognition Myths
Face recognition is one of the most powerful security technologies available, but it’s often misunderstood. Some picture face recognition as a catch-all technology that is detrimental to privacy, conjuring to mind Big Brother in George Orwell’s 1984. There was even news reported recently that half of the U.S. population is in a facial recognition database available to law enforcement. But according to Lloyd Muenzer, a law enforcement technology expert who helps local and federal law enforcement agencies use face recognition, this statistic is wildly exaggerated. Muenzer works at the Automated Regional Justice Information System (ARJIS) in San Diego county, where he maintains a larger face recognition watchlist than most counties. However, he estimates that only a little more than 13% of his county’s inhabitants are enrolled in the system.
While privacy is a concern with any biometric technology, in its report regarding the commercial use of facial recognition technology, the Government Accountability Office (GAO) noted that facial recognition technology is actually less intrusive than traditional video surveillance, in that facial recognition technology only captures biometric information. In fact, face recognition actually prevents profiling by race, age, gender and national origin. Face Recognition Applications
As consumer and enterprise face recognition solutions proliferate, there are a variety of ways that face recognition is currently being used. Here are some of the most prevalent face recognition applications.
Facial recognition is often used with static surveillance cameras. Cameras are typically optimized for angle and lighting conditions in order to capture the best possible image of an individual’s face. After an image is captured, the person’s face is then matched against a database of images and it is determined if that individual potentially matches someone that should be watched. One example is if a person walks into a retail outlet and his face matches that of a known organized retail criminal. Loss prevention professionals could proactively monitor that person. Whereas normal surveillance cameras are only reactive (offering information after crimes occur), facial recognition empowers the loss prevention teams to deter crime. Facial recognition is currently being used for surveillance purposes at retail stores, banks, casinos, sports arenas and more.
Mobile Face Recognition
Mobile face recognition software is often used by patrol officers to identify suspects in the field. For example, if they pull over someone who is speeding, and that person doesn’t have his driver’s license, the officer could snap a photo of the individual and potentially verify his identity and see whether he has any outstanding warrants. This can help officers save a lot of time and keep communities safer.
Face recognition can also be used to send alerts to mobile devices which tell security personnel where to go, who to monitor and what to do. An example is if a dangerous criminal enters a department store, security might see an alert saying not to engage the person and instead to call the police immediately.
Facial recognition technology is sometimes used for geofencing, which uses biometric data to determine who should or shouldn’t be in a particular area. One example of this application is if a bank were to use face recognition to determine which employees have access to sensitive areas.
Phones have already used biometric data in the form of fingerprints to enable access to various applications. Moving forward, face recognition will play a greater role in security, as our phones and other devices begin using face recognition to enable access to various apps.