Syndetics omslagsbild
Bild från Syndetics

Facial Kinship Verification [electronic resource] : A Machine Learning Approach / by Haibin Yan, Jiwen Lu.

Av: Medverkande: Materialtyp: TextSerie: SpringerBriefs in Computer ScienceUtgivningsuppgift: Singapore : Springer Nature Singapore : Imprint: Springer, 2017Utgåva: 1st ed. 2017Beskrivning: 1 online resource (X, 82 p. 33 illus.). 29 illus. in colorInnehållstyp:
  • text
Medietyp:
  • computer
Bärartyp:
  • online resource
ISBN:
  • 9789811044847
Ämnen: Fler format: Printed edition:: Ingen titel; Printed edition:: Ingen titelDDK-klassifikation:
  • 006.37 23
Library of Congress (LC) klassifikationskod:
  • TA1634
Onlineresurser:
Innehåll:
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.
I: Springer Nature eBookSammanfattning: 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.
Inga fysiska exemplar för denna post

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.

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.

Print version record.

Licensed e-book