Investigating deep CNNs models applied in kinship verification through facial images
Chergui, Abdelhakim; Ouchtati, Salim; Mavromatis, Sebastien; Bekhouche, Salah Eddine; Sequeira, Jean (2019-12-23)
A. Chergui, S. Ouchtati, S. Mavromatis, S. E. Bekhouche and J. Sequeira, "Investigating Deep CNNs Models Applied in Kinship Verification through Facial Images," 2019 5th International Conference on Frontiers of Signal Processing (ICFSP), Marseille, France, 2019, pp. 82-87, doi: 10.1109/ICFSP48124.2019.8938055
© 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.
The kinship verification through facial images is ana ctive research topic due to its potential applications. In this paper, we propose an approach which takes two images as input then give kinship result (kinship / No-kinship) as an output. our approach based on the deep learning model (ResNet) for the feature extraction step, alongside with our proposed pair feature representation function and RankFeatures (Ttest) for feature selection to reduce the number of features finally we use the SVM classifier for the decision of kinship verification. The approach contains three steps which are: (1) face preprocessing, (2) deep features extraction and pair features representation (3) Classification. Experiments are conducted on five public databases. The experimental results show that our approach is comparable with existed approaches.
- Avoin saatavuus