Zhang / Chen / Xu Computer Models for Facial Beauty Analysis

1. Auflage 2016
ISBN: 978-3-319-32598-9
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 268 Seiten

Reihe: Computer Science

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 toimplement 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.

Zielgruppe

Research

Autoren/Hrsg.

Zhang, David

Chen, Fangmei

Xu, Yong

Inhaltsverzeichnis

Overview.- Typical Facial Beauty Analysis.- Facial Landmark Model Designs.- Geometrics Facial Beauty Study.- Putative Ratio Rules for Facial Beauty.- Beauty Analysis Fusion Model of Texture and Geometric Features.- Optimal Feature Set for Facial Beauty Analysis.- Examination of Averageness Hypothesis on Large Database.- A New Hypothesis on Facial Beauty Perception.- Beauty Analysis by Learning Machine and Subspace Extension.- Combining a Causal Effect Criterion for Evaluation of Facial Beauty Models.- Data-Driven Facial Beauty Analysis: Prediction, Retrieval and Manipulation.- A Facial Beauty Analysis Simulation System.- Book Review and Future Work.