This document provides an overview of facial recognition systems. It discusses what facial recognition is, which is a computer system that identifies people by analyzing facial features from images and video. It explains that facial recognition started in the 1960s and is now commonly used for security applications. The document outlines different approaches to facial recognition, including two-dimensional and three-dimensional systems, and describes some of the techniques involved like feature extraction and classification. It also provides details about a specific facial recognition product called FA007 and its uses for access control.

2. CONTENTS
 Facial expressions
 What is facial recognition system?
 Why to use?
 Two Dimensional
 Three Dimensional
 Approaches
 FA007

3. FACIAL EXPRESSIONs
The seven universal expressions of emotion

4. WHAT is it?
A facial recognition system is a computer
application for automatically identifying or
verifying a person from a digital image or a
video frame from a video source. One of the
ways to do this is by comparing selected facial
features from the image and a facial database.
Research on this technology started in the mid
1960s.

5. WHY TO USE?
It is typically used in security systems
and can be compared to other
biometrics such as fingerprint or eye
iris recognition systems.

6. Two-Dimensional
 Before the advent of faster computers and
complicated imaging software, two-
dimensional facial recognition systems
were used. The problem that arose from
this type of facial recognition system was
the fact that the person to be identified
must be facing the camera at no more than
35 degrees for accurate identification to be
possible. Light differences and facial
expressions also contributed to low
accuracy in recognition of such systems.

8. Three Dimensional
 The new facial recognition systems make use
of three-dimensional images and are thus
more accurate than their predecessors. Just
like two-dimensional facial recognition
systems, these systems make use of distinct
features in a human face and use them as
nodes to create a face print of a person. Unlike
two-dimensional face recognition systems,
however, they have the ability to recognize a
face even when it is turned 90 degrees away
from the camera. Moreover, they are not
affected by the differences in lighting and
facial expressions of the subject.

9. APPROACHES
 Image Acquisition: Images used for facial expression
recognition are static images or image sequences. An
image sequence contains potentially more information
than a still image
 Pre-Processing: Expression representation can be
sensitive to translation, scaling, and rotation of the
head in an imaged.
 Feature Extraction: Feature extraction converts
pixel data into a higher-level representation- of
shape, motion, color, texture of the face or its
components. The extracted representation is used
for subsequent expression categorization.

10.  Classification: Expression categorization is performed
by a classifier. The two main types of classes used in
facial expression recognition are action units (AUs) and
the prototypic facial expressions defined by Ekman. The
6 prototypic expressions relate to the emotional states
of happiness, sadness, surprise, anger, fear, and
disgust.
 Post-Processing: Post-processing aims to improve
recognition accuracy, by exploiting domain knowledge to
correct classification errors.

12. FA007
 FA007 is an embedded facial
recognition system, which
applied for high level access
control application. Its classic
slope and industrial design is
good for market like
Government, Civil ID. It is also
good for commercial market
like Enterprise, Bank, building
automation and so on.

13. THANKS