Proceedings ArticleDOI
Self-similarity representation of Weber faces for kinship classification
Naman Kohli,Richa Singh,Mayank Vatsa +2 more
- pp 245-250
TLDR
A kinship classification algorithm that uses the local description of the pre-processed Weber face image to outperforms an existing algorithm and yields a classification accuracy of 75.2%.Abstract:
Establishing kinship using images can be utilized as context information in different applications including face recognition. However, the process of automatically detecting kinship in facial images is a challenging and relatively less explored task. The reason for this includes limited availability of datasets as well as the inherent variations amongst kins. This paper presents a kinship classification algorithm that uses the local description of the pre-processed Weber face image. A kinship database is also prepared that contains images pertaining to 272 kin pairs. The database includes images of celebrities (and their kins) and has four ethnicity groups and seven kinship groups. The proposed algorithm outperforms an existing algorithm and yields a classification accuracy of 75.2%.read more
Citations
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Journal ArticleDOI
Kinship verification using multiview hybrid distance learning
Shahar Mahpod,Yosi Keller +1 more
TL;DR: This work proposes a multiview hybrid combined symmetric and asymmetric distance learning network for facial kinship verification, which was successfully applied to the KinFaceW and KinFaceCornell datasets, comparing favorably with contemporary state-of-the-art approaches.
Proceedings ArticleDOI
Kinship verification in the wild: The first kinship verification competition
Jiwen Lu,Junlin Hu,Xiuzhuang Zhou,Jie Zhou,Modesto Castrillón-Santana,José Javier Lorenzo Navarro,Lu Kou,Andrea Bottino,Tiago Figuieiredo Vieira +8 more
TL;DR: The key goal of this competition is to compare the performance of different methods on a new-collected dataset with the same evaluation protocol and develop the first standardized benchmark for kinship verification in the wild.
Proceedings ArticleDOI
KinNet: Fine-to-Coarse Deep Metric Learning for Kinship Verification
TL;DR: In this work, KinNet is proposed, a fine-to-coarse deep metric learning framework for kinship verification, which transfers knowledge from the large-scale-data-driven face recognition task by pre-training the network with massive data for face recognition.
Proceedings ArticleDOI
Deep kinship verification
TL;DR: A novel deep kinship verification (DKV) model is proposed by integrating excellent deep learning architecture into metric learning by employing a deep learning model followed by a metric learning formulation to select nonlinear features.
Proceedings ArticleDOI
Leveraging appearance and geometry for kinship verification
TL;DR: One feature matching scheme to locate familial traits between two facial images and a method using geometry information for kinship verification, which achieves more than 17% improvement compared with the state of the art.
References
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