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Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg http:// graphics.informatik.uni-

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Page 1: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Learning the Appearance of Faces:A Unifying Approach for the Analysis and Synthesis of Images.

Thomas VetterThomas Vetter

Germany GermanyUniversity of FreiburgUniversity of Freiburg

http://graphics.informatik.uni-freiburg.dehttp://graphics.informatik.uni-freiburg.de

Page 2: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Computer Vision & Computer Graphics

Computer Graphics can help to solve Computer Vision!

| G (p) - I |2 = min Parameters

G ( image ) Parameters-1

Vision ( image ) parameters

image Graphics ( parameters )

Page 3: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg
Page 4: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg
Page 5: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Analysis by Synthesis

3DWorld Image

Analysis

Synthesis

Image Model

Image Description

model parameter

Page 6: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Synthesis of Faces

Input ImageInput Image

Modeler

ResultResult

Database

FaceAnalyzer

3D Head3D Head

Morphable

Face Model

Page 7: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Approach: Example based modeling of faces

2D Image 3D Face Models2D Image 3D Face Models

= w1 * + w2 * + w3 * + w4 * +. . .

Page 8: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Cylindrical Coordinates

red(h,)green(h,)

blue(h,)

red(h,)green(h,)

blue(h,)

h

radius(h,)radius(h,)

h

Page 9: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Morphing 3D Faces

3D Blend

3D Morph

1__2

1__2

+ =

Page 10: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Correspondence: A two step process!

Correspondence between

1. two examples ( Optical Flow like algorithms).

2. many examples ( Morphable Model )

Reference

Example

2nd Example

Page 11: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

=

a1 * + a2 * + a3 * + a4 * +. . .

b1 * + b2 * + b3 * + b4 * +. . .

Vector space of 3D faces.

A Morphable Model can generate new faces.

Page 12: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Manipulation of Faces

Modeler

Page 13: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Modelling in Face Space

Caricatur

OriginalOriginal

AverageAverage

Page 14: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Modelling the Appearance of Faces

A face is represented as a point in face space.Which directions code for specific attributes ?

Page 15: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Learning from Labeled Example Faces

Fitting a (linear) regression function

Page 16: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Facial Attributes

WeightWeightWeightWeight

OriginalOriginalOriginalOriginal

Subjective Subjective AttractivenessAttractiveness

Subjective Subjective AttractivenessAttractiveness

Page 17: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Transfer of Facial Expressions

= Smile= Smile--

Originals:Originals:

+ Smile =+ Smile =Novel Face:Novel Face:

Page 18: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Facial Expressions

OriginalOriginalOriginalOriginal

Page 19: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

3D Shape from Images

FaceAnalyzer

3D Head3D HeadInput ImageInput Image

Page 20: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Matching a Morphable 3D-Face-Model

= R

Optimization problem!Optimization problem!Optimization problem!Optimization problem!

a1 * + a2 * + a3 * + a4 * +. .

b1 * + b2 * + b3 * + b4 * +. .

Page 21: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Error Function

• Image difference

• Plausible parameters

• Minimize

priorimage EEE priorimage EEE

2

,inputmodelImage ),(),(

yx

yxyxE II 2

,inputmodelImage ),(),(

yx

yxyxE II

),...),(log(prior ii bapE ),...),(log(prior ii bapE

Page 22: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Optimization Strategies

• Stochastic Gradient Decent

new old

old

i i ci

dEc c i

dc

new old

old

i i ci

dEc c i

dc

I c A I c A

• Difference Decomposition • Difference Decomposition

Page 23: Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter Germany University of Freiburg

Future Challenges

• Which Object Classes are linear ?

• How to built them automatically?