Facial kinship verification: A comprehensive review and outlook

X Wu, X Feng, X Cao, X Xu, D Hu, MB López… - International Journal of …, 2022 - Springer
Abstract The goal of Facial Kinship Verification (FKV) is to automatically determine whether
two individuals have a kin relationship or not from their given facial images or videos. It is an …

A literature survey on kinship verification through facial images

X Qin, D Liu, D Wang - Neurocomputing, 2020 - Elsevier
Kinship verification is an emerging task in computer vision which aims at finding out whether
there is a kin relation between given identities through their facial images. Applications of …

High-order knowledge-based discriminant features for kinship verification

M Khammari, A Chouchane, A Ouamane… - Pattern Recognition …, 2023 - Elsevier
This research work aims to propose an effective and robust face kinship verification system
by leveraging several axes, including advanced learning techniques, deep learning, and …

Sharable and individual multi-view metric learning

J Hu, J Lu, YP Tan - IEEE transactions on pattern analysis and …, 2017 - ieeexplore.ieee.org
This paper presents a sharable and individual multi-view metric learning (MvML) approach
for visual recognition. Unlike conventional metric leaning methods which learn a distance …

Prototype-based discriminative feature learning for kinship verification

H Yan, J Lu, X Zhou - IEEE Transactions on cybernetics, 2014 - ieeexplore.ieee.org
In this paper, we propose a new prototype-based discriminative feature learning (PDFL)
method for kinship verification. Unlike most previous kinship verification methods which …

Visual kinship recognition of families in the wild

JP Robinson, M Shao, Y Wu, H Liu… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
We present the largest database for visual kinship recognition, Families In the Wild (FIW),
with over 13,000 family photos of 1,000 family trees with 4-to-38 members. It took only a …

Tri-subject kinship verification: Understanding the core of a family

X Qin, X Tan, S Chen - IEEE Transactions on Multimedia, 2015 - ieeexplore.ieee.org
One major challenge in computer vision is to go beyond the modeling of individual objects
and to investigate the bi-(one-versus-one) or tri-(one-versus-two) relationship among …

Target detection based on random forest metric learning

Y Dong, B Du, L Zhang - IEEE Journal of selected topics in …, 2015 - ieeexplore.ieee.org
Target detection is aimed at detecting and identifying target pixels based on specific spectral
signatures, and is of great interest in hyperspectral image (HSI) processing. Target detection …

Embedding metric learning into an extreme learning machine for scene recognition

C Wang, G Peng, B De Baets - Expert Systems with Applications, 2022 - Elsevier
Metric learning can be very useful to improve the performance of a distance-dependent
classifier. However, separating metric learning from the classifier learning possibly …

Sequential fusion of facial appearance and dynamics for depression recognition

Q Chen, I Chaturvedi, S Ji, E Cambria - Pattern Recognition Letters, 2021 - Elsevier
In mental health assessment, it is validated that nonverbal cues like facial expressions can
be indicative of depressive disorders. Recently, the multimodal fusion of facial appearance …