Component-based metric learning for fully automatic kinship verification

被引:10
作者
Wu, Huishan [1 ]
Chen, Jiawei [2 ]
Liu, Xiao [2 ]
Hu, Junlin [3 ]
机构
[1] Beijing Language & Culture Univ, Sch Informat Sci, Beijing 100083, Peoples R China
[2] Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China
[3] Beihang Univ, Sch Software, Beijing 100191, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
Kinship verification; Metric learning; Component; Feature combination; Facial image; FACE;
D O I
10.1016/j.jvcir.2021.103265
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper introduces a fully automatic method for kinship verification from facial images. Recently, a number of methods have been proposed to verify kinship from facial images, however, most of these methods are needed to exactly align face images before feature extraction in a manual manner. Unlike these methods, our method does not depend on face alignment. Firstly, we localize several facial feature points by utilizing a facial feature detector to extract SIFT descriptor around each feature point of a face image. Lastly, two ways, feature combination and distance metric learning, are used to verify the kinship of a pair of face images. For feature combination, three simple strategies of feature combination and support vector machine classifier are used for kinship verification. For metric learning, we propose a component-based metric learning (CML) method to measure the distance of each face pair, which jointly learns multiple local distance metrics, and one specific distance metric for each facial feature point. Experimental results show the effectiveness of our proposed approach on two popular kinship datasets.
引用
收藏
页数:6
相关论文
共 28 条
[1]  
[Anonymous], 2011, P INT JOINT C ART IN
[2]  
[Anonymous], 2006, BMVC, DOI DOI 10.5244/C.20.92
[3]   LIBSVM: A Library for Support Vector Machines [J].
Chang, Chih-Chung ;
Lin, Chih-Jen .
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2011, 2 (03)
[4]   A Unified Approach to Kinship Verification [J].
Dahan, Eran ;
Keller, Yosi .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2021, 43 (08) :2851-2857
[5]   TOWARDS COMPUTATIONAL MODELS OF KINSHIP VERIFICATION [J].
Fang, Ruogu ;
Tang, Kevin D. ;
Snavely, Noah ;
Chen, Tsuhan .
2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, 2010, :1577-1580
[6]   Patch-Based Dual-Tree Complex Wavelet Transform for Kinship Recognition [J].
Goyal, Aarti ;
Meenpal, Toshanlal .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 30 :191-206
[7]  
Hu JL, 2019, IEEE IMAGE PROC, P1178, DOI [10.1109/icip.2019.8803754, 10.1109/ICIP.2019.8803754]
[8]   Local Large-Margin Multi-Metric Learning for Face and Kinship Verification [J].
Hu, Junlin ;
Lu, Jiwen ;
Tan, Yap-Peng ;
Yuan, Junsong ;
Zhou, Jie .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2018, 28 (08) :1875-1891
[9]   Sharable and Individual Multi-View Metric Learning [J].
Hu, Junlin ;
Lu, Jiwen ;
Tan, Yap-Peng .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2018, 40 (09) :2281-2288
[10]  
Köstinger M, 2012, PROC CVPR IEEE, P2288, DOI 10.1109/CVPR.2012.6247939