Thông tin tài liệu
3D FACE PROCESSING
Modeling, Analysis and
Synthesis
THE KLUWER INTERNATIONAL SERIES IN
VIDEO COMPUTING
Series Editor
Mubarak Shah, Ph.D.
University of Central Florida
Orlando, USA
Other books in the series:
EXPLORATION OF VISUAL DATA
Xiang Sean Zhou, Yong Rui, Thomas S. Huang; ISBN: 1-4020-7569-3
VIDEO MINING
Edited by Azriel Rosenfeld, David Doermann, Daniel DeMenthon;ISBN: 1-4020-7549-9
VIDEO REGISTRATION
Edited by Mubarah Shah, Rakesh Kumar; ISBN: 1-4020-7460-3
MEDIA
COMPUTING: COMPUTATIONAL MEDIA AESTHETICS
Chitra Dorai and Svetha Venkatesh; ISBN: 1-4020-7102-7
ANALYZING VIDEO SEQUENCES OF MULTIPLE HUMANS: Tracking, Posture
Estimation
and Behavior Recognition
Jun Ohya, Akita Utsumi, and Junji Yanato; ISBN: 1-4020-7021-7
VISUAL EVENT DETECTION
Niels
Haering and Niels da Vitoria Lobo; ISBN: 0-7923-7436-3
FACE
DETECTION AND GESTURE RECOGNITION FOR HUMAN-COMPUTER
INTERACTION
Ming-Hsuan
Yang and Narendra Ahuja; ISBN: 0-7923-7409-6
3D FACE PROCESSING
Modeling, Analysis and
Synthesis
Zhen Wen
University of Illinois at Urbana-Champaign
Urbana, IL, U.S.A.
Thomas S. Huang
University of Illinois at Urbana-Champaign
Urbana, IL, U.S.A.
KLUWER ACADEMIC PUBLISHERS
NEW YORK, BOSTON, DORDRECHT, LONDON, MOSCOW
eBook ISBN: 1-4020-8048-4
Print ISBN: 1-4020-8047-6
Print ©
2004
Kluwer Academic Publishers
All rights reserved
No part of this eBook may be reproduced or transmitted in any form or by any means, electronic,
mechanical, recording, or otherwise, without written consent from the Publisher
Created in the United States of America
Boston
©2004 Springer Science + Business Media, Inc.
Visit Springer's eBookstore at: http://www.ebooks.kluweronline.com
and the Springer Global Website Online at: http://www.springeronline.com
Contents
List of Figures
List of Tables
Preface
Acknowledgments
xi
xv
xvii
xix
1.
INTRODUCTION
1
2
Motivation
Research Topics Overview
2.1
2.2
2.3
2.4
2.5
3D face processing framework overview
3D face geometry modeling
Geometric-based facial motion modeling, analysis and
synthesis
Enhanced facial motion analysis and synthesis using
flexible appearance model
Applications of face processing framework
3
Book Organization
1
2
2
2
4
5
7
8
9
11
11
12
12
13
14
14
15
17
19
2.
3D FACE MODELING
1
State of the Art
1.1
1.2
1.3
Face modeling using 3D range scanner
Face modeling using 2D images
Summary
2
Face Modeling Tools in iFACE
2.1
2.2
Generic face model
Personalized face model
3
Future Research Direction of 3D Face Modeling
3.
LEARNING GEOMETRIC 3D FACIAL MOTION MODEL
vi
3D FACE PROCESSING: MODELING, ANALYSIS AND SYNTHESIS
1
Previous Work
1.1
1.2
1.3
Facial deformation modeling
Facial temporal deformation modeling
Machine learning for facial deformation modeling
2
3
4
5
6
7
Motion Capture Database
Learning Holistic Linear Subspace
Learning Parts-based Linear Subspace
Animate Arbitrary Mesh Using MU
Temporal Facial Motion Model
Summary
4.
GEOMETRIC MODEL-BASED 3D FACE TRACKING
1
Previous Work
1.1
Parameterized geometric models
1.1.1
1.1.2
1.1.3
1.1.4
1.2
1.3
1.3.1
1.3.2
B-Spline curves
Snake model
Deformable template
3D parameterized model
FACS-based models
Statistical models
Active Shape Model (ASM) and Active Appearance
Model (AAM)
3D model learned from motion capture data
2
3
4
Geometric MU-based 3D Face Tracking
Applications of Geometric 3D Face Tracking
Summary
5.
GEOMETRIC FACIAL MOTION SYNTHESIS
1
Previous Work
1.1
1.2
1.3
Performance-driven face animation
Text-driven face animation
Speech-driven face animation
2
3
4
5
Facial Motion Trajectory Synthesize
Text-driven Face Animation
Offline Speech-driven Face Animation
Real-time Speech-driven Face Animation
5.1
Formant features for speech-driven face animation
5.1.1 Formant analysis
19
19
20
21
22
23
24
27
29
30
31
31
32
32
32
33
33
33
34
34
34
35
37
38
41
41
41
42
42
44
46
47
48
49
49
Contents
vii
5.1.2
An efficient real-time speech-driven animation system
based on formant analysis
5.2
ANN-based real-time speech-driven face animation
5.2.1
5.2.2
5.2.3
5.2.4
Training data and features extraction
Audio-to-visual mapping
Animation result
Human emotion perception study
6
Summary
6.
FLEXIBLE APPEARANCE MODEL
1
Previous Work
1.1
1.2
1.3
Appearance-based facial motion modeling, analysis and
synthesis
Hybrid facial motion modeling, analysis and synthesis
Issues in flexible appearance model
1.3.1
1.3.2
1.3.3
Illumination effects of face appearance
Person dependency
Online appearance model
2
Flexible Appearance Model
2.1
Reduce illumination dependency based on illumination
modeling
2.1.1
2.1.2
2.1.3
Radiance environment map (REM)
Approximating a radiance environment map using spherical
harmonics
Approximating a radiance environment map from a
single image
2.2
Reduce person dependency based on ratio-image
2.2.1
2.2.2
2.2.3
Ratio image
Transfer motion details using ratio image
Transfer illumination using ratio image
3
Summary
7.
FACIAL MOTION ANALYSIS USING FLEXIBLE APPEARANCE
MODEL
1
Model-based 3D Face Motion Analysis Using Both Geometry
and Appearance
1.1
1.2
1.3
1.4
Feature extraction
Influences of lighting
Exemplar-based texture analysis
Online EM-based adaptation
50
52
53
53
55
56
59
61
62
62
62
63
63
66
66
67
67
67
68
70
71
71
71
72
73
75
75
77
79
79
80
viii
3D FACE PROCESSING: MODELING, ANALYSIS AND SYNTHESIS
2
3
Experimental Results
Summary
8.
FACE APPEARANCE SYNTHESIS USING FLEXIBLE
APPEARANCE MODEL
1
Neutral Face Relighting
1.1
Relighting with radiance environment maps
1.1.1
1.1.2
1.1.3
1.1.4
Relighting when rotating in the same lighting condition
Comparison with inverse rendering approach
Relighting in different lighting conditions
Interactive face relighting
1.2
Face relighting from a single image
1.2.1
Dynamic range of images
1.3
1.4
Implementation
Relighting results
2
3
Face Relighting For Face Recognition in Varying Lighting
Synthesize Appearance Details of Facial Motion
3.1
3.2
Appearance of mouth interior
Linear alpha-blending of texture
4
Summary
9.
APPLICATION EXAMPLES OF THE FACE PROCESSING
FRAMEWORK
1
Model-based Very Low Bit-rate Face Video Coding
1.1
1.2
1.3
1.4
Introduction
Model-based face video coder
Results
Summary and future work
2
Integrated Proactive HCI environments
2.1
2.2
2.3
Overview
Current status
Future work
3
Summary
10.
CONCLUSION AND FUTURE WORK
1
2
Conclusion
Future Work
2.1
2.2
2.3
Improve geometric face processing
Closer correlation between geometry and appearance
Human perception evaluation of synthesis
83
87
91
91
92
92
93
93
94
94
95
96
97
100
103
103
104
105
107
107
107
108
109
110
110
111
112
113
113
115
115
116
116
116
117
Contents
ix
2.3.1
2.3.2
Previous work
Our ongoing and future work
Appendices
Projection of face images in 9-D spherical harmonic
space
References
Index
117
120
123
125
137
List of Figures
1.1
1.2
2.1
2.2
2.3
2.4
2.5
3.1
3.2
3.3
3.4
3.5
3.6
Research issues and applications of face processing.
A unified 3D face processing framework.
The generic face model. (a): Shown as wire-frame
model. (b): Shown as shaded model.
An example of range scanner data. (a): Range map.
(b): Texture map.
Feature points defined on texture map.
The model editor.
An example of customized face models.
An example of marker layout for MotionAnalysis sys-
tem.
The markers of the Microsoft data [Guenter et al., 1998].
(a): The markers are shown as small white dots. (b) and
(c): The mesh is shown in two different viewpoints.
The neutral face and deformed face corresponding to
the first four MUs. The top row is frontal view and the
bottom row is side view.
(a): NMF learned parts overlayed on the generic face
model. (b): The facial muscle distribution. (c): The
aligned facial muscle distribution. (d): The parts over-
layed on muscle distribution. (e): The final parts de-
composition.
Three lower lips shapes deformed by three of the lower
lips parts-based MUs respectively. The top row is the
frontal view and the bottom row is the side view.
(a): The neutral face side view. (b): The face deformed
by one right cheek parts-based MU.
3
4
14
15
15
16
16
22
23
24
25
26
26
[...]... aspects of 3D face processing, although all these areas are still subject of active research This book introduces the frontiers of 3D face processing techniques It reviews existing 3D face processing techniques, including techniques for 3D face geometry modeling, 3D face motion modeling, 3D face motion tracking and animation Then it discusses a unified framework for face modeling, analysis and synthesis. .. model-based 3D face tracking, and 3D face synthesis such as text- and speech-driven face animation 2.3 Geometric-based facial motion modeling, analysis and synthesis Accurate face motion analysis and realistic face animation demands good model of the temporal and spatial facial deformation One type of approaches use geometric-based models [Black and Yacoob, 1995, DeCarlo and Metaxas, 2000, Essa and Pentland,... we discuss the motivation for 3D face processing research and then give overviews of our 3D face processing research 2 1 3D FACE PROCESSING: MODELING, ANALYSIS AND SYNTHESIS Motivation Human face provides important visual cues for effective face- to -face humanhuman communication In human-computer interaction (HCI) and distant human-human interaction, computer can use face processing techniques to estimate... computer vision and computer graphics A 3D face model lays basis for modelbased face video analysis and facial animations In face video analysis, a 3D face model helps recognition of oblique views of faces [Blanz et al., 2002] Based on the 3D geometric model of faces, facial deformation models can be constructed for 3D non-rigid face tracking [DeCarlo, 1998, Tao, 1999] In computer graphics, 3D face models... (shape) and appearance (texture) in face analysis and synthesis The Active Appearance Model (AAM) [Cootes et al., 1998] and its variants, apply PCA to model both the shape variations of image patches and their texture variations They have been shown to be powerful tools for face alignment, recognition, and synthesis Blanz and Vetter [Blanz and Vetter, 1999] propose 3D morphable models for 3D faces modeling,. .. introduces the motivation and background of 3D face processing research and gives an overview of our research Several research topics will be discussed in more details in the following chapters First, we describe methods and systems for modeling the geometry of static 3D face surfaces Such static models lay basis for both 3D face analysis and synthesis To study the motion of human faces, we propose motion... overview of these 3D face modeling techniques Then we will describe the tools in our iFACE system for building personalized 3D face models The iFACE system is a 3D face modeling and animation system, developed based on the 3D face processing framework It takes the CyberwareTM 3D scanner data of a subject’s head as input and provides a set of tools to allow the user to interactively fit a generic face model... Chapter 6 to enhance the framework We use efficient and effective methods to reduce the the appearance model’ s dependency on illumination and person Then, in Chapter 7 and Chapter 8 we xviii 3D FACE PROCESSING: MODELING, ANALYSIS AND SYNTHESIS present experimental results to show the effectiveness of the flexible appearance model in face analysis and synthesis In Chapter 9, we describe applications in... surface deformation, and (2) how to apply these models for facial deformation analysis and synthesis In this section, we introduce previous research on facial deformation modeling 1.1 Facial deformation modeling In the past several decades, many models have been proposed to deform 3D facial surface spatially Representative models include free-form inter- 20 3D FACE PROCESSING: MODELING, ANALYSIS AND SYNTHESIS. .. Section 3 2 Face Modeling Tools in iFACE We have developed iFACE system which provides functionalities for face modeling and face animation It provides a research platform for the 3D face processing framework The iFACE system takes the CyberwareTMscanner data of a subject’s head as input and allows the user to interactively fit a generic face model to the CyberwareTM scanner data The iFACE system also . motivation for 3D
face processing research and then give overviews of our 3D face processing
research.
2
3D FACE PROCESSING: MODELING, ANALYSIS AND SYNTHESIS
1.
Motivation
Human. the
frontiers of 3D face processing techniques. It reviews existing 3D face process-
ing techniques, including techniques for 3D face geometry modeling, 3D face
motion
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