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FACE RECOGNITION
AND MATH!
MATH THAT’S USED FOR COMPUTERAIDED FACE RECOGNITION:
 Mathematical

modeling
 Algorithms
 3D facial
recognition
 Advantages
 Disadvantages
 Conclusion
THE MATH BEHIND
DIGITAL FACE RECOGNITION
ALGORITHMS
•

Most face recognition algorithms fall
into one of two main groups: featurebased and image-based algorithms.
Feature-based methods explore a set of
geometric features, such as the distance
between the eyes or the size of the eyes,
and use these measures to represent the
given face.
HOW FACIAL RECOGNITION WORKS?
To begin with, a recognition
system has to be unaffected by
both external changes, like
environmental light, and the
person’s position and distance
from the camera, and internal
variations, like facial expression,
aging, and makeup.
3D FACIAL RECOGNITION
•

•

•

Emerging trend in facial recognition software
using a 3D model which provide more accuracy.
It can even be used in darkness and has the
ability to recognize a subject at different view
angles.

Using 3D software ,the system goes through a
series of steps to verify the identity of an
individual.
WORKING STEPS…
• Acquiring an image can be
accomplished by digitally
scanning device.

• Once it detects a face,
the system determines the
head’s position, size and
pose.
WORKING STEPS…
The system measures the
curves of the face on a submillimeter scale and creates
a template.

The system translates the unique
code .
WORKING

STEPS…
If the image is 3D and the
database contains 3D images,
then matching will take place
without any changes being
made to the image.
In verification, an image is
matched to only one image in
the database.
ADVANTAGES
•

•

•

•

Repeat offenders are identified using
facial recovery.
It has been used by Law Enforcement
Agencies to capture random faces in
crowd.
It is used to verify that the person
received the visa is same person
attempting to gain entry.
Easy way to access personal accounts
without remembering passwords.
DISADVANTAGES
•

•

•
•

Variant Pose may occur because
people always don’t orient to camera
Different lighting and quality of
camera may also effect recognition
Invasion of privacy
Too easy to misuse for wrong
purposes
CONCLUSION
The computer based face
recognition industry has made
much useful advancement in past
decade however, the need for
higher accuracy systems remains.
Through the determination and
commitment the progress will
continue, raising the bar for face
recognition technology.
WORK BY:KEJTI CELA
SUBJECT:MATH ADVANCE

DATE:29.1.2014

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Face recognition and math

  • 2. MATH THAT’S USED FOR COMPUTERAIDED FACE RECOGNITION:  Mathematical modeling  Algorithms  3D facial recognition  Advantages  Disadvantages  Conclusion
  • 3. THE MATH BEHIND DIGITAL FACE RECOGNITION
  • 4. ALGORITHMS • Most face recognition algorithms fall into one of two main groups: featurebased and image-based algorithms. Feature-based methods explore a set of geometric features, such as the distance between the eyes or the size of the eyes, and use these measures to represent the given face.
  • 5. HOW FACIAL RECOGNITION WORKS? To begin with, a recognition system has to be unaffected by both external changes, like environmental light, and the person’s position and distance from the camera, and internal variations, like facial expression, aging, and makeup.
  • 6. 3D FACIAL RECOGNITION • • • Emerging trend in facial recognition software using a 3D model which provide more accuracy. It can even be used in darkness and has the ability to recognize a subject at different view angles. Using 3D software ,the system goes through a series of steps to verify the identity of an individual.
  • 7. WORKING STEPS… • Acquiring an image can be accomplished by digitally scanning device. • Once it detects a face, the system determines the head’s position, size and pose.
  • 8. WORKING STEPS… The system measures the curves of the face on a submillimeter scale and creates a template. The system translates the unique code .
  • 9. WORKING STEPS… If the image is 3D and the database contains 3D images, then matching will take place without any changes being made to the image. In verification, an image is matched to only one image in the database.
  • 10. ADVANTAGES • • • • Repeat offenders are identified using facial recovery. It has been used by Law Enforcement Agencies to capture random faces in crowd. It is used to verify that the person received the visa is same person attempting to gain entry. Easy way to access personal accounts without remembering passwords.
  • 11. DISADVANTAGES • • • • Variant Pose may occur because people always don’t orient to camera Different lighting and quality of camera may also effect recognition Invasion of privacy Too easy to misuse for wrong purposes
  • 12. CONCLUSION The computer based face recognition industry has made much useful advancement in past decade however, the need for higher accuracy systems remains. Through the determination and commitment the progress will continue, raising the bar for face recognition technology.
  • 13. WORK BY:KEJTI CELA SUBJECT:MATH ADVANCE DATE:29.1.2014