Computer Models for Facial Beauty Analysis

Computer Models for Facial Beauty Analysis

EnglishPaperback / softbackPrint on demand
Zhang, David
Springer, Berlin
EAN: 9783319813233
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Detailed information

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.
EAN 9783319813233
ISBN 3319813234
Binding Paperback / softback
Publisher Springer, Berlin
Publication date April 22, 2018
Pages 268
Language English
Dimensions 235 x 155
Country Switzerland
Readership General
Authors Chen Fangmei; Xu Yong; Zhang, David
Illustrations 141 Illustrations, black and white; XV, 268 p. 141 illus.
Edition Softcover reprint of the original 1st ed. 2016
Manufacturer information
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