人脸具有多特征的属性，是人类表达和交流的最重要、最直接的载体。通过人脸可以判断出一个人的美丑，甚至身份等信息；人们还能通过人脸丰富而复杂细小的变化，得到对方的情绪状态，以及相关的病理信息。本书探讨具有四种不同的人脸主要特征及其相应的应用，即固有个体特征的人脸识别，固有群体特征的美学分析，疾病导致变化特征的医学诊断，以及外界刺激形成变化特征的表情鉴别。对于这些不同的人脸特征及应用，本书重点介绍包括获取数据样本、提取表述特征和匹配决策判断等内容，并在大量训练的数据库上分别验证其研究的有效性。 本书研究基础扎实，内容翔实、严谨。可作为面部特征识别领域研究人员的专业用书，也可供计算机图像识别、生物识别等专业研究生参考使用。

前辅文
Chapter 1 Introduction
  1.1 Why Faces with Multi-Characteristics
  1.2 Facial Authentication Using Permanent Special Features
  1.3 Facial Beauty Analysis Using Permanent Common Features
  1.4 Facial Diagnosis by Disease Changed Features
  1.5 Expression Recognition by Stimulus Changed Features
  1.6 Outline of This Book
  References
PART I FACIAL AUTHENTICATION
  Chapter 2 Facial Authentication Overview
   2.1 Introduction
   2.2 Permanent Unique Features for Facial Recognition
   2.3 Facial Recognition: Systems and Applications
   2.4 Chapters Overview
   2.5 Summary
   References
  Chapter 3 Evolutionary Discriminant Feature Based Facial Recognition
   3.1 Introduction
   3.2 Evolutionary Discriminant Feature Extraction
   3.3 Facial Recognition Experiments
   3.4 Summary
   References
  Chapter 4 Facial Identification by Gabor Feature Based Robust Representation
   4.1 Introduction
   4.2 Related Work
   4.3 Gabor-Feature Based Robust Representation and Classification
   4.4 Experimental Results
   4.5 Discussion of Regularization on Coding Coefficients
   4.6 Summary
   References
  Chapter 5 Three Dimension Enhanced Facial Identification
   5.1 Introduction
   5.2 Joint Face Alignment and 3D Face Reconstruction
   5.3 Application to Face Recognition
   5.4 Experiments
   5.5 Summary
   References
PART II FACIAL BEAUTY ANALYSIS
  Chapter 6 Facial Beauty Analysis Overview
   6.1 Introduction
   6.2 Permanent Common Features for Beauty Analysis
   6.3 Facial Beauty Analysis: Features and Systems
   6.4 Chapters Overview
   6.5 Summary
   References
  Chapter 7 Facial Beauty Analysis by Geometric Features
   7.1 Introduction
   7.2 Related Work
   7.3 Proposed Geometric Beauty Analysis Framework
   7.4 Experiments on the Proposed Dataset
   7.5 Experiment on M2B Dataset
   7.6 Discussion
   7.7 Summary
   References
  Chapter 8 Facial Beauty Analysis by Landmark Model
   8.1 Introduction
   8.2 Related Work
   8.3 Key Point (KP) Definition
   8.4 Inserted Point (IP) Generation
   8.5 The Optimized Landmark Model
   8.6 Comparison with Other LMs
   8.7 Applications
   8.8 Summary
   References
  Chapter 9 A New Hypothesis for Facial Beauty Analysis
   9.1 Introduction
   9.2 Notations and the New Hypothesis
   9.3 Empirical Proof of the WA Hypothesis
   9.4 Corollary of the Hypothesis and Convex Hull-Based Face Beautification
   9.5 Compatibility with Other Hypotheses
   9.6 Summary
   References
  Chapter 10 Facial Beauty Analysis: Prediction, Retrieval and Manipulation
   10.1 Introduction
   10.2 Facial Image Preprocessing and Feature Extraction
   10.3 Facial Beauty Modeling
   10.4 Facial Beauty Prediction
   10.5 Beauty-Oriented Face Retrieval
   10.6 Facial Beauty Manipulation
   10.7 Experiments
   10.8 Summary
   References
PART III FACIAL DIAGNOSIS
  Chapter 11 Facial Diagnosis Overview
   11.1 Introduction
   11.2 Disease Changing Features for Facial Diagnosis
   11.3 Computerized Facial Diagnosis
   11.4 Chapters Overview
   11.5 Summary
   References
  Chapter 12 Non-Invasive Diabetes Mellitus Detection Using Facial Colors
   12.1 Introduction
   12.2 Facial Images and Dataset
   12.3 Facial Block Color Feature Extraction
   12.4 Healthy Versus DM Classification with the SRC
   12.5 Experimental Results
   12.6 Discussion
   12.7 Summary
   References
  Chapter 13 Health Status Analysis by Facial Texture Features
   13.1 Introduction
   13.2 Facial Image Acquisition Device
   13.3 Facial Image Pre-Processing and the Dataset
   13.4 Facial Image Texture Features Extraction
   13.5 Classification
   13.6 Experiments
   13.7 Summary
   References
  Chapter 14 Computerized Facial Diagnosis Using Both Color and Texture Features
   14.1 Introduction
   14.2 Facial Image Dataset
   14.3 Facial Feature Extraction
   14.4 Healthy Classification Using Facial Gloss
   14.5 Facial Block-Based Disease Analysis
   14.6 Summary
   References
PART IV FACIAL EXPRESSION RECOGNITION
  Chapter 15 Expression Recognition Overview
   15.1 Introduction
   15.2 Stimulus Changed Features for Expression Recognition
   15.3 Facial Expression Recognition: Systems and Applications
   15.4 Chapters Overview
   15.5 Summary
   References
  Chapter 16 Expression Recognition by Supervised LLE
   16.1 Introduction
   16.2 Independent Component Analysis
   16.3 Supervised Locally Linear Embedding
   16.4 Experiments
   16.5 Summary
   References
  Chapter 17 Expression Recognition on Multiple Manifolds
   17.1 Introduction
   17.2 Multi-Manifold Based Facial Expression Recognition
   17.3 Experiments and Discussion
   17.4 Summary
   References
  Chapter 18 Cross Domain Facial Expression Recognition
   18.1 Introduction
   18.2 A Transfer Learning Based Approach
   18.3 A Discriminative Feature Adaptation Approach
   18.4 Summary
   References
  Chapter 19 Book Review and Future Work
   19.1 Book Recapitulation
   19.2 Challenges and Future Work
  Index
  插图