University of Oulu

A. Chergui, S. Ouchtati, S. Mavromatis, S. Eddine Bekhouche, J. Sequeira and H. Zerrari, "Kinship Verification using Mixed Descriptors and Multi Block Face Representation," 2019 International Conference on Networking and Advanced Systems (ICNAS), Annaba, Algeria, 2019, pp. 1-6, doi: 10.1109/ICNAS.2019.8807875

Kinship verification using mixed descriptors and multi block face representation

Saved in:
Author: Chergui, Abdelhakim1; Ouchtati, Salim1; Mavromatis, Sebastien2;
Organizations: 1LRES Laboratory of skikda August 20th, 1955 University Skikda, Algeria
2LIS Laboratory (UMR CNRS 7020) Aix Marseille University Marseille, France
3Center for Machine Vision and Signal Analysis University of Oulu, Finland Oulu, Finland
4Automatic Laboratory of Skikda August 20th, 1955 University Skikda, Algeria
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.6 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2020051229451
Language: English
Published: Institute of Electrical and Electronics Engineers, 2019
Publish Date: 2020-05-12
Description:

Abstract

Kinship verification is a challenging problem that recently attracted much interest in computer vision, this system has a number of applications such as organizing large collections of images and recognizing resemblances among humans and search for lost people. In this work, we propose a new method based on different descriptors mixed such as (LBP, LPQ, BSIF), and the Multi-Block (MB) representation. and we investigate the effect of different features representation for kinship verification, Moreover, the use of TTest to reduce the number of features and the support vector machine (SVM) for the kinship classification. Our approach consists of five stages: (1) features extraction, (2) face representation (3) features representation, (4) features selection and (5) classification. Our approach is tested on five datasets (Cornell, UB Kin Face, Familly 101, KinFac W-I and W-II). Our results are good comparable with other approaches.

see all

ISBN: 978-1-7281-2642-5
ISBN Print: 978-1-7281-2643-2
Pages: 34 - 39
DOI: 10.1109/ICNAS.2019.8807875
OADOI: https://oadoi.org/10.1109/ICNAS.2019.8807875
Host publication: 2019 International Conference on Networking and Advanced Systems (ICNAS)
Conference: International Conference on Networking and Advanced Systems
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
Subjects:
LBP
LPQ
MB
SVM
Copyright information: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.