29-06-2012, 06:04 PM
AVERAGE HALF FACE RECOGNITION
AVERAGE HALF FACE RECOGNITION.pptx (Size: 448 KB / Downloads: 31)
Introduction
Face recognition has been extensively researched and has recently received much interest. This is partly due to recent efforts in improving security, such as automatic surveillance and the use of biometrics in identification.
Why Average Half Face Recognition?
Security
Fight terrorism
Find fugitives
Personal information access
ATM
Sporting events
Home access (no keys or passwords)
Any other application that would want personal identification
Improved human-machine interaction
Personalized advertising
Beauty search
What Is Difficult About Average Half Face Recognition
Lighting variation
Orientation variation (face angle)
Size variation
Large database
Processor intensive
Time requirements
More Modern Approaches
Among appearance-based methods eigenfaces and fisher faces have been proved effective in experiments involving large databases.
Feature-based graph matching approaches have been successful as well, and are less sensitive to variations in illumination and viewpoint, as well as inaccuracy in face localization.
Feature extraction techniques in graph matching approaches are currently inadequate.
Example: cannot detect an eye if the eyelid is closed.