Face recognition uses the spatial geometry of distinguishing features of the face. It is a form of computer vision that uses the face to identify or to authenticate a person.
An important difference with other biometric solutions is that faces can be captured from some distance away, with for example surveillance cameras. Therefore face recognition can be applied without the subject knowing that he is being observed. This makes face recognition suitable for finding missing children or tracking down fugitive criminals using surveillance cameras.
- A digital camera acquires an image of the face.
- Software locates the face in the image, this is also called face detection. Face detection is one of the more difficult steps in face recognition, especially when using surveillance cameras for scanning an entire crowd of people.
- When a face has been selected in the image, the software analyzes the spatial geometry. The techniques used to extract identifying features of a face are vendor dependent. In general the software generates a template, this is a reduced set of data which uniquely identifies an individual based on the features of his face.
- The generated template is then compared with a set of known templates in a database (identification) or with one specific template (authentication).
- The software generates a score which indicates how well two templates match. It depends on the software how high a score must be for two templates to be considered as matching, for example an authentication application requires low FAR and thus the score must be high enough before templates can be declared as matching. In a surveillance application however you would not want to miss out on any fugitive criminals thus requiring a low FRR, so you would set a lower matching score and security agents will sort out the false positives.
APPLICATION OF FACE RECOGNITION
Face recognition can be used together with surveillance cameras to automatically identify missing children, unwanted subjects in casino’s or fugitive criminals for which a picture is registered in a central database.
Different solutions exist for both small and large businesses, as well as for private use, that apply face recognition for access control to computer systems. Furthermore as custom solutions for border control and physical access control.
SUITABILITY OF FACE RECOGNITION
How suitable is face recognition as a biometric solution? We use the following 7 criteria to evaluate the suitability of face recognition:
|Universality||For some people face recognition might not work as well as for others. For example long hair or a beard might give face recognition systems extra difficulty, and not all marketed solutions will deal with this equally well.|
|Uniqueness||Face recognition cannot distinguish identical twins.|
|Permanence||As you age your face will most likely change. Also injury, plastic surgery or more temporary changes such as sunglasses, make-up or growing a beard might have an impact.|
|Collectability||Faces are easy to collect, direct contact with the biometric device is not required and the subject might not even know that an image of his face is being collected.|
|Acceptability||There certainly are privacy concerns when using a surveillance system to track people’s whereabouts. However applying face recognition for access control will be easier accepted than other biometric solutions because no direct contact is required with a reader, and in general people do not consider taking a photograph as being intrusive as might be the case with biometric solutions such as iris recognition or fingerprint recognition.|
|Circumvention||This is very much dependent on the technical implementation, much depends on the quality of the camera, the control of the surroundings (e.g. background) and on the matching algorithm. Some biometric authentication applications based on face recognition include a liveness check, for example by requesting the subject to blink with his eyes.|
|Performance||Speed might be an issue for surveillance systems, imagine having the matching algorithm verifying the faces of travelers on an airport: a high number of verifications with images that are taken without subjects looking directly into the camera.|
We can conclude that face recognition is most interesting because the subject is not necessarily aware that his identity is being verified, this is very useful for surveillance applications. Circumvention is an important factor to consider when choosing face recognition for authentication purposes, furthermore permanence and uniqueness of the face might remain a limitting factor of this biometric solution.
Like all biometrics solutions, face recognition technology measures and matches the unique characteristics for the purposes of identification or authentication. Often leveraging a digital or connected camera, facial recognition software can detect faces in images, quantify their features, and then match them against stored templates in a database.
Face scanning biometric tech is incredibly versatile and this is reflected in its wide range of potential applications.
Where do I find facial recognition?
Face biometrics have the potential to be integrated anywhere you can find a modern camera. Law enforcement agencies the world over use biometric software to scan faces in CCTV footage, as well as to identify persons of interest in the field. Border control deployments use face recognition to verify the identities of travelers. It even has consumer applications.
Thanks to its software based nature, face recognition tech has paved the way for selfie-based authentication on smartphones. Banking apps (like the one offered by USAA), payment apps (like MasterCard’s video selfie system) and simply logical access control—these are all made possible on any mobile device with a front facing camera.
We are also seeing face biometrics in the digital world, with Facebook, ShutterStock, and other social platforms that seek to organize incredible amounts of rich image data by identifying the people captured in them.
How is facial recognition making a difference?
Facial recognition doesn’t just deal with hard identities, but also has the ability to gather demographic data on crowds. This has made face biometrics solutions much sought after in the retail marketing industry.