图书简介
What features or information can we observe from a face, and how can these information help us to understand the person concerned, in terms of their well-being and what can we learn about and from each given feature? This book answers these questions by first dividing a face’s multiple characteristics into two main categories: original (or physiological) features and features that change over a lifetime. The first category, original features, may be further divided into two sub-classes: features special (or unique) to an individual, and features common to a particular group. The second, changed features, can also be subdivided into two groups: features altered due to disease or features altered by other external factors. From these four sub-categories, four different applications — facial identification using original and special features; beauty analysis using original common features; facial diagnosis by disease changed features; and expression recognition through affect-changed features — are identified.
The book will benefit researchers, professionals, and graduate students working in the field of computer vision, pattern recognition, security/clinical practice, and beauty analysis, and will also be useful for interdisciplinary research.
Key Features:
o Unique book focusing on computational aspects of Boolean networks
o Provide computational foundations on Boolean networks
o Contain recent and up-to-date results on algorithms for Boolean networks
Part 1: Introduction: Why Face with Multi-Characteristics; Facial Identification in Original Special Features; Beauty Analysis in Original Common Features; Facial Diagnosis by Disease Changed Features; Expression Recognition by Effect Changed Features; Outline of this Book; Facial Identification; Special Original Features for Facial Identification; Systems and Applications; Facial Recognition by Evolutionary Discriminant Features; Evolutionary Discriminant Feature Extraction (EDFE); Bagging EDFE; Facial Identification Experiments; Facial Identification by Gabor Feature based Robust Representation; Gabor-Feature based Robust Representation and Classification; Discussion of Regularization on Coding Coefficients; Facial Identification Using 3D Features; Part 2: Facial Beauty Analysis: Common Original Features for Beauty Analysis; Facial Beauty Analysis by Geometric Features; Human Face Shape Space Modeling; Quantitative Analysis; Landmark Model; Inserted Point (IP) Generation; Optimized Landmark Model; Comparison with Other LMs; New Hypothesis for Facial Beauty Analysis; Empirical Proof of the WA Hypothesis; Corollary of the Hypothesis and Convex Hull-Based Face Beautification; Compatibility with Other Hypotheses; Prediction, Retrieval and Manipulation; Facial Image Preprocessing and Feature Extraction; Facial Beauty Modeling; Facial Beauty Prediction; Beauty-Oriented Face Retrieval; Facial Beauty Manipulation; ;Part 3: Facial Diagnosis: Disease Changed Features for Facial Diagnosis; Non-Invasive Diabetes Mellitus Detection using Facial Colors; Facial Images and Dataset; Facial Block Color Feature Extraction; Healthy Versus DM Classification with an SRC; Health Status Analysis by Facial Texture Features; Facial Image Capture Device; Facial Image Pre-Processing and the Dataset; Facial Image Texture Features Extraction; Classification; Computerized Facial Diagnosis using both Color and Texture Features; Facial Image Dataset; Facial Feature Extraction; Healthy Classification using Facial Gloss; Facial Block-Based Disease Analysis; Part 4: Facial Expression Recognition: Effect Changed Features for Expression Recognition; Expression Recognition by Supervised LLE; Expression Recognition on Multiple Manifolds; Cross-Domain Facial Expression Recognition using Discriminative Feature Adaptation;
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