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Kinship Verification from Faces via Similarity Metric Based Convolutional Neural Network

  • Lei Li
  • Xiaoyi Feng
  • Xiaoting Wu
  • Zhaoqiang Xia
  • Abdenour Hadid
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9730)

Abstract

The ability to automatically determine whether two persons are from the same family or not is referred to as Kinship (or family) verification. This is a recent and challenging research topic in computer vision. We propose in this paper a novel approach to kinship verification from facial images. Our solution uses similarity metric based convolutional neural networks. The system is trained using Siamese architecture specific constraints. Extensive experiments on the benchmark KinFaceW-I & II kinship face datasets showed promising results compared to many state-of-the-art methods.

Keywords

Kinship verification Similarity metric learning Convolutional neural networks Siamese architecture 

Notes

Acknowledgments

The financial support of the Academy of Finland, Infotech Oulu, Nokia Foundation, the Northwestern Polytechnical University, and the Shaanxi Province is acknowledged.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Lei Li
    • 1
  • Xiaoyi Feng
    • 1
  • Xiaoting Wu
    • 1
  • Zhaoqiang Xia
    • 1
  • Abdenour Hadid
    • 1
    • 2
  1. 1.School of Electronics and InformationNorthwestern Polytechnical UniversityXi’anChina
  2. 2.Center for Machine Vision Research (CMVS)University of OuluOuluFinland

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