Post on 19-Dec-2015
Outline
•The advantages of algorithm
•SVD in a nutshell
•The methodology
•Results from a number of images
•The result of interest points algorithm
•The algorithem’s errors
: The algorithm is robust relative to
• Changes in lighting
• Eye color and complexion
• Blurring
• Introduction of glasses
• Different resolutions
• Complex background
• Variability in scale and orientation
Eye Detection
The algorithm proceeds in four steps :
1. Variance reduction
2. Application of SVD transform with a nonlinear function f
3. Application of edge detection algorithm
4. Separation of boundary edges
f= 1/(1+s(t)) for t=1,..,8
Original Image
SVD transform uses the exponential of a linear function of diagonal part of the SVD decomposition.
SVD Transform in diffident coefficients of the sigma in the SVD
Using Edge Detection
Using noise removal
- =minus equal
The Methodology