University of São Paulo
Institute of Mathematics and Statistics
Department of Computer Science
Tracking Facial Features Using Gabor Tracking Facial Features Using Gabor Wavelet NetworksWavelet Networks
Rogério Schmidt Feris
Roberto Marcondes Cesar Junior{rferis,cesar}@ime.usp.br
OutlineOutline
Motivation
Wavelet Transforms
Face Representation Using GWNs
Facial Feature Tracking
Experimental Results
Future Work
MotivationMotivation
Face Recognition from Video Sequences
Problem Assumptions
Wavelet TransformsWavelet Transforms
Continuous Wavelet Transform
Discrete Wavelet Transform
Wavelet Networks
f x w xi ni
i
~
( ) ( )
Face Representation Using GWNsFace Representation Using GWNs
)2()2
1exp()( xusinxxx TT
Mother Wavelet: Odd-Gabor Function
Face Representation Using GWNsFace Representation Using GWNs
cossin
sin-cos RRotation
ysDilation
0
0sS
x
y
x
c
cc nTranslatio
))(()( cxSRxn
},...,,{21 Mnnn
),,,,( yxyx ssccn
Face Representation Using GWNsFace Representation Using GWNs2
,)(min
i
niiwn
fwfEi
ii
Original Image Wavelet Representation
Wavelet parameters are chosen from the continuous parameters space !!
Face Representation Using GWNsFace Representation Using GWNs
Progressive Attention
Interest32, 52, 100 and 320 wavelets
Direct Calculation of Weights
Facial Feature TrackingFacial Feature Tracking
Repositioning
Facial Feature TrackingFacial Feature Tracking
Superwavelet
))(()( cxSRwxi
nin i
),,,,,( xyyxyx sssccn
y
xyx
s
ssS
0
Reparametrization
2min n
ngE
Facial Feature TrackingFacial Feature Tracking
Initialization
Repositioning in each Frame
Facial Feature Tracking
2min
tt
ntn
JE
Experimental ResultsExperimental Results
Efficiency and Robustness
http://www.ime.usp.br/~rferis
Future WorkFuture Work
Tracking Based on Wavelet Weights
Face Detection Using GWNs
3D Wavelet Model
Experimental ResultsExperimental Results
http://www.ime.usp.br/~rferis
Efficiency and Robustness
