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.
1. Introduction to Facial Kinship Verification.- 2. Feature Learning for Facial Kinship Verification.- 3. Metric Learning for Facial Kinship Verification.- 4. Video-Based Facial Kinship Verification.- 5. Conclusions and Future Work.
Dr. Haibin Yan received her B.Eng. and M.Eng. degrees from the Xi'an University of Technology, Xi'an, China, in 2004 and 2007, and her Ph.D. degree from the National University of Singapore in 2013, all in mechanical engineering. She is currently an assistant professor at the School of Automation, Beijing University of Posts and Telecommunications, China. From October 2013 to July 2015, she was a research fellow at the Department of Mechanical Engineering, National University of Singapore, Singapore. Her research interests include pattern recognition and robotic vision. She has published more than 20 papers in major journals, such as the IEEE Transactions on Cybernetics, the IEEE Transactions on Information Forensics and Security, and Image and Vision Computing. Hl£)
![Facial Kinship Verification A Machine Learning Approach [Paperback]](/itemImage/2/4/0/3/2_1000010.jpg)