Facial recognition technology refers to a computer driven application that automatically identifies.
Facial recognition technology refers to a computer driven application that automatically identifies an individual from his or her digital image by a comparison of particular facial features in a facial database and in the live image (“Face Recognition,” 2007). The technology creates a template of people’s facial configurations, such as the lengths of their noses and the angles of their jaws. It thereby functions like the other biometric technologies (e. g. iris scanning) that use biological features for the purposes of recognition.
According to Visionics, a manufacturer of face recognition technology, this technology is capable of finding human faces “anywhere in the field of view and at any distance, and it can continuously track them and crop them out of the scene, matching the face against a watch list” (Kautzer). While iris scanning and other kinds of biometric technologies are known to be far more accurate than the face recognition technology, it is believed that the latter would be more widely accepted because it is least intrusive.
The technology also does not require users to push, click, or insert anything into the system. Moreover, companies using the face recognition technology do not require the installation of anything except the new software application. The cameras in place as well as the pictures of their employees on file are enough for companies that use the technology. Hence, face recognition technology is cheaper for organizations than the iris scanning, for instance, which requires reading setups.
According to Frances Zelazney of Visionics, yet another advantage of facial recognition technology as compared to the other biometric technologies is that “[unlike] other biometrics, facial recognition provides for inherent human backup because we naturally recognize one another… If the system goes down, someone can pull out an ID with a picture as backup, something you can’t do with fingerprint devices (Rutherford, 2001). ” Unsurprisingly, facial recognition technology is known as the fastest growing biometric technology in our day.
Law enforcement agencies and the military have been using the technology successfully for many years without the public being aware of it. In the year 1988, the Los Angeles County Sheriff’s Department (Lakewood Division) began using composite sketches of suspects, as well as video images, in order to conduct searches on a database of digital facial shots. The department also has a photo database of sex offenders, and plans to find suspects on this database.
Then there is the Gang Reporting Evaluation Tracking system that can be searched with the use of photos of suspects in order for law enforcement to circumvent false identification cards as well as information that has been presented by gang members (Jarvis). There are numerous United States embassies around the world that are already using the face recognition technology to keep criminals from entering the country. The Israel-Palestine border control is similarly equipped with the technology to reduce crime across the border (Jarvis).
IQ Biometrix, established in 2001, is a company providing help to thousands of law enforcement agencies around the world with the FACESTM, which is a groundbreaking software tool allowing for the “creation and recreation of billions of facial images, as well as their encoding, cataloging and transmitting. ” The technology incorporates a facial composite tool that the FBI and the CIA also use. The United States Department of Defense, the U. S. Navy, and various local as well as state police agencies have similarly opted for this groundbreaking system of facial recognition (IQ Biometrix, 2004).
Given the importance of putting a name to a face, whether it is to solve crimes, protect the public, or to ensure security in jails, face recognition technology is proving itself to be of tremendous value. Sheriff Everett Rice along with the Pinellas County Sheriff’s Office in Florida employs the Viisage face recognition technology to “positively identify and verify individuals. ” Some of these individuals have just been recently arrested, while others are about to released. The face recognition technology is also of use with people that visit the courthouse.
So far, the application of the technology has been successful, and users of the technology believe that it would have a greater impact on crime control in the years to come (“Facial Recognition,” 2007). The United States Department of Defense, with its focus on perfecting the face recognition technology to spot criminals at the borders of the nation, had been funding scientists’ research on the technology for more than decade. Private companies were similarly convinced that the face recognition technology could help dramatically in combating crime within the borders of the United States.
Because of their belief, the marketing of the technology became widespread during the mid-1990s (Rutherford). Then came 9/11 – the day that changed the security concerns of the entire world in the matter of only a few hours. There was increased interest in face recognition technology following the terrorist attacks on the American soil. Although the Americans had viewed the face recognition technology with skepticism before the attacks, they became confident that widespread use of the new technology in security as well as public safety would help protect them from similar attacks in future.
Indeed, the face recognition technology could play an important role in the prevention of tragedies. All the same, law enforcement agencies have discovered that in the areas covered by the new technology, no terrorist has ever been identified. What is more, despite the redoubling of efforts to create dependable face recognition systems after 9/11, the technology suffers from problems. The facial recognition technology faces a difficulty, for example, in the recognition of the effects of aging.
Digitally compared photos of individuals that had been taken eighteen months apart produced untrue rejections by the software application at least forty three percent of the time. Furthermore, it has been found that the technology is more successful when used by casinos to identify cheaters; in welfare offices; and by driver’s license bureaus, given the uniformity of lighting and the use of the same cameras in these places (Jarvis; O’Harrow, 2001).
Seeing that the face recognition technology is not fool proof, albeit useful – and security experts have confirmed this – it is best to use it at the sporting event only to augment security measures. The new technology can help security personnel at the sporting event to spot terrorists, for instance. However, face recognition technology should not be considered a replacement for traditional security measures by any means. What is more, this technology is easy to use, and security personnel would not have a difficult time installing and working through the system.
Hence, the use of face recognition technology at the sporting event is definitely recommended as a boost to the traditional security measures. References Face Recognition System. (2007). Wikipedia. Retrieved 25 August 2007, from http://en. wikipedia. org/wiki/Facial_recognition_system. Facial Recognition in Action. (2007). Penton Media. Retrieved 25 August 2007, from http://govtsecurity. com/current/. Jarvis, A. Are Privacy Rights of Citizens Being Eroded Wholesale? Forensic Evidence.
Retrieved 25 August 2007, from http://forensic-evidence. com/site/ID/facialrecog. html. Kautzer, C. Face Recognition Technology. ZMAG. Retrieved 25 August 2007, from http://www. zmag. org/ZMag/articles/march02kautzer. htm. O’Harrow, R. (2001, August 1). Matching Faces With Mug Shots. Washington Post, p. A01. Rutherford, Emelie. (2001, July 17). Facial Recognition Tech Has People Pegged. CNN. Retrieved 25 August 2007, from http://www. cnn. com/2001/TECH/ptech/07/17/face. time. idg.