
Computer Models for Facial Beauty Analysis
Springer (Publisher)
Published on 22. April 2018
Book
Paperback/Softback
XV, 268 pages
978-3-319-81323-3 (ISBN)
Description
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.
More details
Edition
Softcover reprint of the original 1st ed. 2016
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
141 s/w Abbildungen
XV, 268 p. 141 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 16 mm
Weight
435 gr
ISBN-13
978-3-319-81323-3 (9783319813233)
DOI
10.1007/978-3-319-32598-9
Schweitzer Classification
Other editions
Additional editions

David Zhang | Fangmei Chen | Yong Xu
Computer Models for Facial Beauty Analysis
Book
04/2016
Springer
€106.99
Shipment within 10-15 days
Persons
David Zhang is currently a professor at the Department of Computing, the Hong Kong Polytechnic University where he is the Founding Director of Biometrics Research Centre (UGC/CRC) supported by the Hong Kong SAR Government. He is the book editor of Springer's International Series on Biometrics (KISB); organizer of the first International Conference on Biometrics Authentication (ICBA); associate editor of more than ten international journals including IEEE Transactions; technical committee chair of the IEEE SMC and the author of more than 10 books and 350 international journal papers. He was listed as a Highly Cited Researcher in Engineering by Thomas Reuters in 2014 and 2015. Professor Zhang is a Croucher senior research fellow, distinguished speaker of the IEEE Computer Society, and a fellow of both the IEEE and IAPR.
Yong Xu currently is a professor at the School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), China. His interests include pattern recognition, biometrics, machine learning, video analysis and bioinformatics. Dr. Xu has designed a number of algorithms for the above fields and has provided effective solutions for real-world pattern and computer vision problems. He has published more than 100 international journal papers, including more than 10 ISI highly cited papers. His prestigious research group has received several awards. Dr. Xu is an associate editor of the International Journal of Image and Graphics, and a senior member of the IEEE. He has published two monographs in English, including Computer Models for Facial Beauty Analysis by Springer, and Advanced Pattern Recognition Technologies with Applications to Biometrics by Medical Information Science Reference.
Wangmeng Zuo currently is a professor at the School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. His research interests include discriminative learning, deep learning, image modeling and low-level vision, and biometrics. Dr. Zuo has published more than 50 papers in leading academic journals and at conferences. Dr. Zuo is an associate editor of the IET Biometrics, guest editor of Neurocomputing, Pattern Recognition, and IEEE Transactions on Circuits and Systems for Video Technology. He has co-authored a book on medical biometrics and several book chapters on biometrics.
Content
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.