Proceedings ArticleDOI
Self-similarity representation of Weber faces for kinship classification
Naman Kohli,Richa Singh,Mayank Vatsa +2 more
- pp 245-250
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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
Tri-Subject Kinship Verification: Understanding the Core of A Family
TL;DR: In this paper, a relative symmetric bilinear model (RSBM) is introduced to model the similarity between the child and the parents, by incorporating the prior knowledge that a child may resemble one particular parent more than the other.
Proceedings ArticleDOI
The FG 2015 Kinship Verification in the Wild Evaluation
Jiwen Lu,Junlin Hu,Venice Erin Liong,Xiuzhuang Zhou,Andrea Bottino,Ihtesham Ul Islam,Tiago Figueiredo Vieira,Xiaoqian Qin,Xiaoyang Tan,Songcan Chen,Shahar Mahpod,Yosi Keller,Lilei Zheng,Khalid Idrissi,Christophe Garcia,Stefan Duffner,Atilla Baskurt,Modesto Castrillón-Santana,Javier Lorenzo-Navarro +18 more
TL;DR: Most of the participants tackled the image-restricted challenge and experimental results demonstrated better kinship verification performance than the baseline methods provided by the organizers.
Journal ArticleDOI
Ensemble similarity learning for kinship verification from facial images in the wild
TL;DR: Experiments results demonstrate that the proposed Ensemble similarity learning (ESL) method is superior to some state-of-the-art methods in terms of both verification rate and computational efficiency.
Journal ArticleDOI
Hierarchical Representation Learning for Kinship Verification
TL;DR: In this paper, a hierarchical kinship verification via representation learning (KVRL) framework is utilized to learn the representation of different face regions in an unsupervised manner, and a compact representation of facial images of kin is extracted as an output from the learned model and a multi-layer neural network is employed to verify the kin accurately.
Journal ArticleDOI
Kinship verification using neighborhood repulsed correlation metric learning
TL;DR: This paper presents a neighborhood repulsed correlation metric learning (NRCML) method for kinship verification via facial image analysis by using the correlation similarity measure where the kin relation of facial images can be better highlighted.
References
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