Facial Kinship Verification - A Machine Learning Approach (Paperback, 1st ed. 2017)

This book provides the first systematic study of facial kinship verification, a new research topic in biometrics. It presents three key aspects of facial kinship verification: 1) feature learning for kinship verification, 2) metric learning for kinship verification, and 3) video-based kinship verification, and reviews state-of-the-art research findings on facial kinship verification. Many of the feature-learning and metric-learning methods presented in this book can also be easily applied for other face analysis tasks, e.g., face recognition, facial expression recognition, facial age estimation and gender classification. Further, it is a valuable resource for researchers working on other computer vision and pattern recognition topics such as feature-learning-based and metric-learning-based visual analysis.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	SpringerBriefs in Computer Science
Release date:	June 2017
First published:	2017
Authors:	Haibin Yan • Jiwen Lu
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	82
Edition:	1st ed. 2017
ISBN-13:	978-981-10-4483-0
Categories:	Books > Computing & IT > Applications of computing > Pattern recognition Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Books > Computing & IT > Applications of computing > Image processing > General
LSN:	981-10-4483-X
Barcode:	9789811044830

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