Computer Models for Facial Beauty Analysis - Hardcover

Zhang, David; Chen, Fangmei; Xu, Yong

Hardcover

ISBN 10: 3319325965 ISBN 13: 9783319325965

Verlag: Springer, 2016

Inhaltsangabe

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.

Über diesen Titel

Über die Autorin bzw. den Autor

Feng Liu is currently an Assistant Professor at the School of Computer Science & Software Engineering, Shenzhen University. She received her Ph.D. degree from the Department of Computing at the Hong Kong Polytechnic University in 2014. Her research interests include pattern recognition and image processing, with a particular focus on fingerprints. Qijun Zhao received his Ph.D. from The Hong Kong Polytechnic University in 2010; his M.Sc. and B.Sc. from Shanghai Jiao Tong University in 2003 and 2006, respectively; and completed his postdoc at Michigan State University in 2010-2012. He is a Professor at Sichuan University's College of Computer Science, and a Visiting Professor at the School of Information Science and Technology at Tibet University (2019-2020). His research is in the fields of pattern recognition, image processing, computer vision and biometrics. David Zhang is a Presidential Chair Professor at the Chinese University of Hong Kong (Shenzhen). He was a Chair Professor at the Hong Kong Polytechnic University, where he has been the Founding Director of the Biometrics Research Centre (UGC/CRC), supported by the Hong Kong SAR Government, since 2005. Currently he also serves as Visiting Chair Professor at Tsinghua University and HIT, and Adjunct Professor at Shanghai Jiao Tong University, Peking University, National University of Defense Technology and the University of Waterloo. Over the past 40 years, he has worked on pattern recognition, image processing and biometrics, and has received various awards for his research developments, including palmprint recognition, computerized TCM and facial beauty analysis. Prof. Zhang is one of the best-known international experts in the field of biometrics and he has published over 20 monographs, 480 international journal papers and 40 patents in USA/Japan/HK/China. He was listed as a Highly Cited Researcher in Engineering by Clarivate Analytics in 2014, 2015, 2016, 2017 and2018, respectively. He is also ranked about 80 in the top 1,000 scientists for international computer science and electronics. Professor Zhang is a Croucher Senior Research Fellow, Distinguished Speaker of the IEEE Computer Society, and a Fellow of both IEEE and IAPR.

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Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2016
• Sprache: Englisch
• ISBN 10: 3319325965
• ISBN 13: 9783319325965
• Einband: Gebundene Ausgabe
• Auflage: 1
• Anzahl der Seiten: 283
• Kontakt zum Hersteller: GPSR Kontakt; ProductSafety@springernature.com; ; Slevogtstraße 3-5; Heidelberg; 69126; Deutschland