Facial recognition technology works by measuring nodal points on faces such as the distance between the eyes and shape of cheekbones. These points are compared to a database of pictures to find a match. It is used in security systems and can identify people passing by cameras. While it provides security benefits, concerns include privacy issues with mass surveillance and systems being fooled by disguises or lighting/camera angle changes. Recent improvements have made algorithms over 100 times more accurate than in 1995 and able to outperform humans in some cases.

1. Facial Recognition Technology
Avinash Kumar Singh
School Of Mechanical Engineering
Kalinga Institute Of Industrial Technology
Bhubaneswar (INDIA)

2. Contents
 What is Face Recognition?
 How Does it Works?
 Pros of Face Recognition system
 Cons Of Face Recognition System
 Where Can You Find It?
 Recent improvements
 On Your Part
Avinash

3. What is Face Recognition?
Avinash

4.  Facial recognition systems are computer-based
security systems that are able to automatically
detect and identify human faces.
The development stage for facial recognition
began in the late 1980s and commercially
available systems were made available in the
1990s. While many people first heard about
facial recognition after September
11th, 2001, football fans were introduced to it
at the 2004 Super Bowl.
Keyboard and/or
Computer
Joystick
Viewer
I

5. How Does It Works?
 The first step for a facial recognition system
is to recognize a human face and extract it
fro the rest of the scene.
 Next, the system measures nodal points on
the face, (such as the distance between the
eyes, the shape of the cheekbones and other
distinguishable features.)

6.  These nodal points are then compared to
the nodal points computed from a database
of pictures in order to find a match
Standalone PTZ cam
– Zoom out to overwatch the scene, and zoom in
to track down an intruding object;
– Easy installation and an ideal operation mode.

7. Template Matching Method
 Store a template
– Predefined: based on edges or regions
 Deformable: based on facial contours (e.g., Snakes)
 Templates are hand-coded (not learned)
 Use correlation to locate faces

8. Pros Of Face Recognition System
 Typically used in security systems and can be
compared to other biometrics such
as fingerprint or eye iris recognition systems
 Face recognition systems can be installed to
require a person to explicitly step up to a camera
and get their picture taken, or to automatically
survey people as they pass by a camera. The
later mode allows for scanning of many people
at the same time

9. Privacy V.S. National Security
 The main issue concerning face recognition is
Privacy V.S. National Security
 Giving your consent to be scanned in order to live
in a safer place.

10. Cons Of face Recognition System
Wavering Backgrounds Birds Flapping
Crowd
Rain
Intelligent Video Surveillance, Penpower Technology

11.  Such systems may be fooled by
hats, beards, sunglasses and face masks
 Even changes of lighting and camera angle
can have a significant effect on the accuracy
of 2D systems
 Some people view mass-scale facial
recognition cameras as the ultimate “big
brother.”

12. System Configuration

13. Where Can You Find It?
 Mostly installed at (indoor)
exits, entrances, passages;
 In addition to motion-sensitive analytics, also
powered by face detection module for quick
capture of human faces in the scene;
 ATM machines-Face recognition at ATM
machines prevents fraud identification and
eliminates the usage of a personal
identification number (PIN)

14. Mission Impossible
. Facial Disguise?
-Only possible in
Hollywood.
-Also too expensive.

15. Recent Improvement
 In 2010, the performance of the latest face
recognition algorithms were evaluated in
the Face Recognition Grand Challenge (FRGC).
High-resolution face images, 3-D face
scans, and iris images were used in the tests.
The results indicated that the new algorithms
are 10 times more accurate than the face
recognition algorithms of 2002 and 100 times
more accurate than those of 1995. Some of the
algorithms were able to outperform human
participants in recognizing faces and could
uniquely identify identical twins

16. Scene and Scenario Database
 Cameras: high sensitivity
 Illumination change: Cont. change v.s. sudden
change, indoor and outdoor, partial and
overall;
 Distance and range (view tilted from horizon
0~90o, object sized from tens of pixels to 90%
of window. )

17. Questions Welcomed!!