Upcoming SlideShare
×

# Face recognition and math

1,296 views
950 views

Published on

®Kejticela

0 Likes
Statistics
Notes
• Full Name
Comment goes here.

Are you sure you want to Yes No
Your message goes here
• Be the first to comment

• Be the first to like this

Views
Total views
1,296
On SlideShare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
44
0
Likes
0
Embeds 0
No embeds

No notes for slide

### Face recognition and math

1. 1. FACE RECOGNITION AND MATH!
2. 2. MATH THAT’S USED FOR COMPUTERAIDED FACE RECOGNITION:  Mathematical modeling  Algorithms  3D facial recognition  Advantages  Disadvantages  Conclusion
3. 3. THE MATH BEHIND DIGITAL FACE RECOGNITION
4. 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. 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. 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. 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. 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. 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. 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. 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. 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. 13. WORK BY:KEJTI CELA SUBJECT:MATH ADVANCE DATE:29.1.2014