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.
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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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Li, L., Feng, X., Wu, X., Xia, Z., Hadid, A. (2016). Kinship Verification from Faces via Similarity Metric Based Convolutional Neural Network. In: Campilho, A., Karray, F. (eds) Image Analysis and Recognition. ICIAR 2016. Lecture Notes in Computer Science(), vol 9730. Springer, Cham. https://doi.org/10.1007/978-3-319-41501-7_60
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DOI: https://doi.org/10.1007/978-3-319-41501-7_60
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