Kinship verification using mixed descriptors and multi block face representation
Chergui, Abdelhakim; Ouchtati, Salim; Mavromatis, Sebastien; Bekhouche, Salah Eddine; Sequeira, Jean; Zerrari, Houssem (2019-08-22)
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
© 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.
https://rightsstatements.org/vocab/InC/1.0/
https://urn.fi/URN:NBN:fi-fe2020051229451
Tiivistelmä
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.
Kokoelmat
- Avoin saatavuus [31941]