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2016 | Buch

Computer Models for Facial Beauty Analysis

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Über dieses Buch

This book covers the key advances in computerized facial beauty analysis, with an emphasis on data-driven research and the results of quantitative experiments. It takes a big step toward practical facial beauty analysis, proposes more reliable and stable facial features for beauty analysis and designs new models, methods, algorithms and schemes while implementing a facial beauty analysis and beautification system. This book also tests some previous putative rules and models for facial beauty analysis by using computationally efficient mathematical models and algorithms, especially large scale database-based and repeatable experiments.The first section of this book provides an overview of facial beauty analysis. The base of facial beauty analysis, i.e., facial beauty features, is presented in part two. Part three describes hypotheses on facial beauty, while part four defines data-driven facial beauty analysis models. This book concludes with the authors explaining how to implement their new facial beauty analysis system.This book is designed for researchers, professionals and post graduate students working in the field of facial beauty analysis, computer vision, human-machine interface, pattern recognition and biometrics. Those involved in interdisciplinary fields with also find the contents useful. The ideas, means and conclusions for beauty analysis are valuable for researchers and the system design and implementation can be used as models for practitioners and engineers.

Inhaltsverzeichnis

Frontmatter

Introduction

Frontmatter
Chapter 1. Overview
Abstract
The physical beauty of faces affects many social outcomes. The secrets of facial beauty have attracted the attention of researchers from many fields. Recently, computer-based facial beauty analysis has become an emerging research topic, which has many potential applications.
David Zhang, Fangmei Chen, Yong Xu
Chapter 2. Typical Facial Beauty Analysis
Abstract
As an interdisciplinary research topic facial beauty can be investigated understood from many aspects.
David Zhang, Fangmei Chen, Yong Xu

Facial Images and Features

Frontmatter
Chapter 3. Facial Landmark Model Design
Abstract
It is clear that practicable facial beauty analysis should start from extraction of features closely associated with facial beauty.
David Zhang, Fangmei Chen, Yong Xu
Chapter 4. Geometrics Facial Beauty Study
Abstract
This chapter for facial beauty analysis mainly presents our studies on extraction and normalization of facial geometric features, one important kind of features for facial beauty analysis, as well as model evaluation and statistical analysis of facial beauty.
David Zhang, Fangmei Chen, Yong Xu
Chapter 5. Putative Ratio Rules for Facial Beauty Indexing
Abstract
Chapters 3 and 4 have shown the significance of geometric features in facial beauty analysis.
David Zhang, Fangmei Chen, Yong Xu
Chapter 6. Beauty Analysis Fusion Model of Texture and Geometric Features
Abstract
Most of previous studies use only one kind of features for facial beauty analysis.
David Zhang, Fangmei Chen, Yong Xu
Chapter 7. Optimal Feature Set for Facial Beauty Analysis
Abstract
Because a number of features have been proposed for facial beauty analysis, it is significant to compare them under the same conditions. This is very useful for people to grasp advantages and shortcomings of different features and can provide guidance to the selection of features.
David Zhang, Fangmei Chen, Yong Xu

Hypotheses on Facial Beauty Perception

Frontmatter
Chapter 8. Examination of Averageness Hypothesis on Large Database
Abstract
The averageness hypothesis is one of the most known hypotheses.
David Zhang, Fangmei Chen, Yong Xu
Chapter 9. A New Hypothesis on Facial Beauty Perception
Abstract
The studies in Chap. 8 show that the averageness hypothesis is in general effective with respect to facial geometric feature driven perception of facial beauty.
David Zhang, Fangmei Chen, Yong Xu

Computational Models of Facial Beauty

Frontmatter
Chapter 10. Beauty Analysis by Learning Machine and Subspace Extension
Abstract
Compared with features based methods, dedicated data-driven facial beauty modeling methods have a major advantage that it may be able to directly perform facial beauty analysis from raw data.
David Zhang, Fangmei Chen, Yong Xu
Chapter 11. Combining a Causal Effect Criterion for Evaluation of Facial Beauty Models
Abstract
As a data-driven facial beauty modeling method, evolutionary cost-sensitive extreme learning machine presented in Chap. 10 shows the potential of the machine learning methodology in facial beauty analysis.
David Zhang, Fangmei Chen, Yong Xu
Chapter 12. Data-Driven Facial Beauty Analysis: Prediction, Retrieval and Manipulation
Abstract
In this chapter, we present a generalized data-driven facial beauty analysis framework that contains three application modules, prediction, retrieval, and manipulation.
David Zhang, Fangmei Chen, Yong Xu

Application System

Frontmatter
Chapter 13. A Facial Beauty Analysis Simulation System
Abstract
Precedent chapters provide solid bases for system design and implementation on facial beauty analysis. These bases include various facial features, models, rules and decision making algorithms for beauty analysis. This chapter introduces our face beautification system, which is very useful and many readers will be interested in. In order to assess the face beauty index, we established this face beauty prediction model and system based on the Geo + PCANet method, which can quickly and effectively estimate beauty indexes for new images. In terms of face beautification, we mainly achieve three functions. First, the shape of the face contour, mouth, eyes, nose, and eyebrows are represented by facial landmark points. We propose a method that can effectively adjust the positions of the landmark points to beautify the facial geometry. Then, we improve the moving least squares (MLS) method to warp the original face image by virtue of the new landmark positions and obtain the beautification result. Second, this system enable us to perform face skin beautification, including face speckle removal, wrinkle removal, skin whitening, etc. The system uses the improved multi-level median filtering for face skin beautification. Third, the average face beautification is implemented. We propose a simple method to achieve average face beautification. Experimental results showed that the proposed system can significantly improve facial attractiveness of most of face images.
David Zhang, Fangmei Chen, Yong Xu
Chapter 14. Book Review and Future Work
Abstract
With the title “Computer Models for Facial Beauty Analysis” this book mainly focus on building computation models for analysis and prediction of the face beauty.
David Zhang, Fangmei Chen, Yong Xu
Backmatter
Metadaten
Titel
Computer Models for Facial Beauty Analysis
verfasst von
David Zhang
Fangmei Chen
Yong Xu
Copyright-Jahr
2016
Electronic ISBN
978-3-319-32598-9
Print ISBN
978-3-319-32596-5
DOI
https://doi.org/10.1007/978-3-319-32598-9

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