智能动画的现代方法：理论和实践（英文版）

　　Part of the new series， Advanced Topics in Science and Technology in China， this book discusses concepts， theory， and core technologies of intelligent theory and human animation， including video based human animation， and intelligent technology of motion data management and reusing. It introduces systems developed to demonstrate the technologies of video based animation. Each chapter is independent. Lively pictures and demos will be presented to make the theory and technologies more understandable. For researchers， this is a reference book and an update on the current status of human animation. For professionals， this is a guide for application development using human animation technologies.

　　Yueting Zhuang received his PhD in Computer Science from Zhejiang University （1998）. From 1997 to 1998， he was a visiting scholar at Beckman Institute， U. of Illinois， Urbana-Champaign. Now he is a full professor of the College of Computer Science at Zhejiang University. His research area is intelligent animation， multimedia technologies. Yunhe Pan was the President of Zhejiang University from 1995 to 2006. Now he is the Vice-President of the Chinese Academy of Engineering. ttis current research area includes intelligent human animation， digital library， and other related topics.

1　Introduction
1.1 Traditional Computer Animation Techniques
1.1.1 Key-frame Animation
1.1.2 Articulated Animation
1.1.3 Facial Expression Animation
1.2 Motion Capture Based Animation Techniques
1.2.1 Definition of Motion Capture
1.2.2 Introduction of Motion Capture Techniques
1.2.3 Summarization
1.3 Motion Editing and Reuse Techniques
1.3.1 Key-frame Editing
1.3.2 Motion Warping
1.3.3 Per-frame Editing
1.3.4 Per-frame Motion Editing Combing Filters
1.3.5 Spatio-temporal Constraint Based Motion Editing
1.3.6 Physical Property Based Motion Editing
1.4 Data-driven Animation Techniques
1.4.1 Data Synthesis Oriented Character Animation
1.4.2 Environment Sensitive Character Animation
1.5 Intelligent Animation
1.5.1 Characteristics and Requirements of Intelligent Animation
1.5.2 Overview of Video-based Intelligent Animation Techniques
References
2　Natural Video-based Human Motion Capture
2.1 Human Motion Capture Based on FeatureTracking
2.1.1 Human Skeleton Model
2.1.2 Feature Tracking in 2D Image Sequence
2.1.3 Reconstruction of 3D Human Motion Sequence
2.1.4 VBHASV1.0
2.1.5 Discussions
2.2 Human Motion Capture Based on Silhouette
2.2.1 Overview
2.2.2 Silhouette Extraction and Analysis
2.2.3 Pose Recovery
2.2.4 Motion Recovery
2.2.5 Results
2.2.6 Discussions
References
3　Human Motion Capture Using Color Markers
3.1 Tracking Color Markers
3.1.1 Human Model and Color Space
3.1.2 Kalman Filter
3.1.3 Edge Detection and Edge Extraction
3.1.4 Rectangle Construction
3.1.5 Block Matching Algorithm
3.2 3D Recovery of Human Motion Data
3.2.1 Two-step Calibration
3.2.2 Selection of Start Points
3.2.3 Solving for Other Joints
3.3 Case Studies: VBHAS V2.0
3.3.1 Results of Human Motion Tracking
3.3.2 Results of Human Motion 3D Reconstruction
References
4　Two-camera-based Human Motion Capture
4.1 Human Model
4.2 Human Motion Feature Tracking
4.2.1 Feature Tracking Algorithms Based on Kalman Filter and Epipolar Constraint
4.2.2 Feature Tracking Based on Attribute Quantification
4.2.3 Incomplete Motion Feature Tracking Algorithm in Video Sequences
4.2.4 Human Motion Tracking in Video via HMM
4.3 3D Motion Reconstruction
4.3.1 Tsai Single Camera Linear Calibration Algorithm
4.3.2 Nonlinear and Non-coplanar Calibration Model
4.3.3 3D Reconstruction of Motion Sequences
4.4 Case Studies: VBHAS V3.0
4.4.1 Camera Calibration
4.4.2 Feature Tracking
4.4.3 3D Reconstruction
References
5　Video-based Facial Animation Techniques
6 Intelligent Techniques for Processing and Management of Motion Data
7 Intelligent Motion Data Reusing Techniques
8 Intelligent Techniques for Character Animation
Index