5 steps of Facial Recognition!

As a biometric, facial recognition is a form of computer vision that uses faces
to attempt to identify a person or verify a person’s claimed identity. Regardless
of specific method used, facial recognition is accomplished in a five step process.

1. First, an image of the face is acquired. This acquisition can be accomplished
by digitally scanning an existing photograph or by using an electro-optical
camera to acquire a live picture of a subject. As video is a rapid sequence of
individual still images, it can also be used as a source of facial images.

2. Second, software is employed to detect the location of any faces in the
acquired image. This task is difficult, and often generalized patterns of what
a face “looks like” (two eyes and a mouth set in an oval shape) are employed
to pick out the faces.

3. Once the facial detection software has targeted a face, it can be analyzed. As
noted in slide three, facial recognition analyzes the spatial geometry of
distinguishing features of the face. Different vendors use different methods
to extract the identifying features of a face. Thus, specific details on the
methods are proprietary. The most popular method is called Principle
Components Analysis (PCA), which is commonly referred to as the eigenface
method. PCA has also been combined with neural networks and local feature
analysis in efforts to enhance its performance. Template generation is the
result of the feature extraction process. A template is a reduced set of data
that represents the unique features of an enrollee’s face. It is important to
note that because the systems use spatial geometry of distinguishing facial
features, they do not use hairstyle, facial hair, or other similar factors.

4. The fourth step is to compare the template generated in step three with those
in a database of known faces. In an identification application, this process
yields scores that indicate how closely the generated template matches each
of those in the database. In a verification application, the generated template
is only compared with one template in the database – that of the claimed
identity.

5. The final step is determining whether any scores produced in step four are
high enough to declare a match. The rules governing the declaration of a
match are often configurable by the end user, so that he or she can determine
how the facial recognition system should behave based on security and
operational considerations.