Biometrics and Facial Recognition
Biometrics is a form of bioinformatics that uses biological properties to identify individuals. Examples of biometrics are fingerprinting, facial recognition, iris scanning, signature authentication, voice recognition and hand geometry. Facial recognition is simply using characteristics of the face to identify an individual.
There are several practical reasons for favoring facial recognition over other biometrics for the purposes of identification. Since the biometric data can be captured at a distance, it does not require active participation on the part of the subject - the individual need not pose, push a button or click a mouse to activate a system, stare into a lens or press an ink pad. Facial Recognition is unobtrusive and discrete. The infrastructure for its implementation is already widespread and inexpensive. Security cameras are common in airports, ATM machines, or at any location a business owner, governmental agency or private homeowner may choose to keep secure. Every government agency and many private companies keep photo ID records. In addition, intelligence agencies have massive surveillance databases of images and video. There is a growing need to match these legacy photos to live individuals: for example, to check that someone is authorized to enter a building, that the user of a debit card is the owner of that card, or that someone entering the country does not match a photo of a known or suspected terrorist.
Unfortunately, current facial recognition technology suffers from failure rates too high to be implemented more pervasively. Most facial recognition applications today use 2-dimensional technology, which measures height, width and distance between feature points to make an identification. This technique introduces a fundamental flaw since faces are 3-dimensional, with irregularly shaped features - noses, lips, ears, hair - that change in appearance as the face turns. Faces also reflect light and produce shadows, essentially creating new and different images. With 2-dimensional technology, failure rates rise with changes in pose or expression or variable lighting.
In 2002 the US Government's Defense Advanced Research Projects Agency (DARPA) and the National Institute of Standards and Technology (NIST) conducted a Facial Recognition Vendor Test. Vendors with facial recognition applications competed with their individual technologies. The failure level was disappointing and unacceptable. The conclusion of the test was that 3-dimensional technology is the only hope to significantly improve the performance of existing facial recognition solutions.
Animetrics is the first company to solve critical problems associated with facial recognition. Our software, which is based on new 3-dimensional technology, addresses variations in (1) pose, (2) lighting and (3) facial expressions. It can be used with any camera, making it cheaper to implement than 3D solutions that require specialized cameras. Our software is fast, and it is approaching real-time speed.
Biometrics is the science of using biological properties to identify individuals. Examples of biometrics include fingerprinting, facial recognition, iris scans, signature authentication, voice recognition and hand geometry. Facial recognition has obvious advantages for personal identification: unlike other biometrics, it is non-invasive, unobtrusive and discrete.
At present the demand for Facial Recognition technologies are fueled by the needs of Homeland Security. With improvements in reliability, future applications will come increasingly from the commercial sector. Applications for Facial Recognition are varied and vast:
- document control (digital chip in passports, drivers' licenses);
- transactional authentication (credit cards, ATMs, point-of-sale);
- computer security (user access verification);
- physical access control (smart doors);
- voter registration (election accuracy);
- time and attendance (entry and exit verification);
- computer games (a virtual "you" plays against virtual opponents)