Kinship Verification Using Facial Images by Robust Similarity Learning
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-01-21
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Kinship verification from face images is a new and challenging problem in pattern recognition and computer vision, and it has many potential real-world applications including social media analysis and children adoptions.
Most existing methods for kinship verification assume that each positive pair of face images (with kin relationship) has greater similarity score than those of negative pairs without kin relationships under a distance metric to be learned.
In practice, however, this assumption is usually too strict for real-life kin samples.
Instead, we propose in this paper learning a robust similarity model, under which the similarity score of each positive pair is greater than average similarity score of some negative ones.
In addition, we develop an online similarity learning algorithm for more scalable application.
We empirically evaluate the proposed methods on benchmark datasets, and experimental results show that our method outperforms some state-of-the-art kinship verification methods in terms of verification accuracy and computational efficiency.
American Psychological Association (APA)
Xu, Min& Shang, Yuanyuan. 2016. Kinship Verification Using Facial Images by Robust Similarity Learning. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1112140
Modern Language Association (MLA)
Xu, Min& Shang, Yuanyuan. Kinship Verification Using Facial Images by Robust Similarity Learning. Mathematical Problems in Engineering No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1112140
American Medical Association (AMA)
Xu, Min& Shang, Yuanyuan. Kinship Verification Using Facial Images by Robust Similarity Learning. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1112140
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112140