Facial expression responsible for controlling the expression differ in each case. Voluntary facial expressions are often socially conditioned and follow a cortical route in the brain. Conversely, involuntary facial expressions are believed to be innate and follow a subcortical route in the brain. Facial recognition is often an emotional experience for the brain and the amygdala is highly involved in the recognition process. The eyes are often viewed as important features of facial expressions. Aspects such as blinking rate can possibly be used to indicate whether a person is nervous or whether he or she is lying. Also, eye contact is considered
Facial recognition system the face data. One of the earliest successful systems is based on template matching techniques applied to a set of salient facial features, providing a sort of compressed face representation. Recognition algorithms can be divided into two main approaches, geometric, which looks at distinguishing features, or photometric, which is a statistical approach that distills an image into values and compares the values with templates to eliminate variances. Some classify these algorithms into two broad categories: holistic and feature-based models. The former attempts to recognize the face in its entirety while the feature-based subdivide into components such as according to features