This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
8/16/99
Computer Vision and ModelingComputer Vision and Modeling
8/16/99
Principal Components with SVDPrincipal Components with SVD
8/16/99
Linear Dimension Reduction:Linear Dimension Reduction:
High-dimensionalInput Space
8/16/99
Linear Subspace:Linear Subspace:
+=
+ 1.7=
8/16/99
Linear Subspace:Linear Subspace:
8/16/99
Principal Components Analysis:Principal Components Analysis:
xWy ~
N
nT mnys
1
22 )][(
TN
nT xxS )~()~(
1
TTT WWSs 2
m
8/16/99
Examples:Examples:
Data:
Kirby, Weisser, Dangelmayer 1993
8/16/99
Examples:Examples:
Data:
PCA
New Basis Vectors
8/16/99
Examples:Examples:
Data:
PCA
EigenLips
8/16/99
Examples:Examples:
Face Recognition with Eigenfaces (Turk+Pentland, ):