Facial Kinship Verification: A Comprehensive Review and Outlook
Reads0
Chats0
TLDR
A comprehensive review of the state-of-the-art methods for Facial Kinship Verification (FKV) can be found in this paper , where the authors identify gaps in current research and discuss potential future research directions.Abstract:
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 emerging and challenging problem that has attracted increasing attention due to its practical applications. Over the past decade, significant progress has been achieved in this new field. Handcrafted features and deep learning techniques have been widely studied in FKV. The goal of this paper is to conduct a comprehensive review of the problem of FKV. We cover different aspects of the research, including problem definition, challenges, applications, benchmark datasets, a taxonomy of existing methods, and state-of-the-art performance. In retrospect of what has been achieved so far, we identify gaps in current research and discuss potential future research directions. read more
Citations
More filters
Journal ArticleDOI
An unbiased kinship estimation method for genetic data analysis
TL;DR: UKin this article proposed an unbiased estimation method, UKin, which can reduce kinship estimation bias by using the observed allele frequencies to calculate both the expectations and variances of genotypes.
Journal ArticleDOI
A robust kinship verification scheme using face age transformation
TL;DR: Wang et al. as discussed by the authors proposed a face age transformation model to generate facial images of various age groups and constructed a cross-age kinship verification model constructed using the generated images as a training dataset.
Journal ArticleDOI
A Comprehensive survey on ear recognition: Databases, approaches, comparative analysis, and open challenges
Amir Benzaoui,Yacine Khaldi,Rafik Bouaouina,Nadia Amrouni,Hammam A. Alshazly,Abdeldjalil Ouahabi +5 more
TL;DR: In this article , the authors present a taxonomy of ear recognition methods, including 2D, 3D, and combined 2D and 3D methods, as well as an overview of historical advances in this field.
Journal ArticleDOI
Easy pair selection method for Kinship Verification using fixed age group images
TL;DR: Zhang et al. as mentioned in this paper proposed a new scheme called easy-pair selection method for kV, which categorized the non-kin pairs into easy and hard pairs based on sum of square distance with respect to the feature space of the pairs.
Journal ArticleDOI
Dual Convolutional Neural Network Classifier with Pyramid Attention Network for Image-Based Kinship Verification
TL;DR: Zhang et al. as discussed by the authors proposed a dual convolutional neural network (CNN) with a pyramid attention network for image-based kinship verification problems, which is formed by paralleling the FaceNet CNN architecture followed by family-aware features extraction network and three final fully connected layers.
References
More filters
Journal ArticleDOI
A Computational Approach to Edge Detection
TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
Proceedings Article
Auto-Encoding Variational Bayes
Diederik P. Kingma,Max Welling +1 more
TL;DR: A stochastic variational inference and learning algorithm that scales to large datasets and, under some mild differentiability conditions, even works in the intractable case is introduced.
Journal ArticleDOI
A comparative study of texture measures with classification based on featured distributions
TL;DR: This paper evaluates the performance both of some texture measures which have been successfully used in various applications and of some new promising approaches proposed recently.
Journal ArticleDOI
Face recognition: A literature survey
TL;DR: In this paper, the authors provide an up-to-date critical survey of still-and video-based face recognition research, and provide some insights into the studies of machine recognition of faces.
Proceedings ArticleDOI
DeepFace: Closing the Gap to Human-Level Performance in Face Verification
TL;DR: This work revisits both the alignment step and the representation step by employing explicit 3D face modeling in order to apply a piecewise affine transformation, and derive a face representation from a nine-layer deep neural network.
Related Papers (5)
Analyzing Data Reusability of Raytrace Application in Splash2 Benchmark
Hao Do-Duc,Vinh Ngo-Quang +1 more