Publication: Face Hallucination with Linear Regression Model in Semi-Orthogonal Multilinear PCA Method
Issued Date
2018-04-25
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ISSN
17426596
17426588
17426588
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2-s2.0-85047819979
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Mahidol University
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SCOPUS
Bibliographic Citation
Journal of Physics: Conference Series. Vol.1004, No.1 (2018)
Suggested Citation
Krissada Asavaskulkiet Face Hallucination with Linear Regression Model in Semi-Orthogonal Multilinear PCA Method. Journal of Physics: Conference Series. Vol.1004, No.1 (2018). doi:10.1088/1742-6596/1004/1/012016 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/47368
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Title
Face Hallucination with Linear Regression Model in Semi-Orthogonal Multilinear PCA Method
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Abstract
© Published under licence by IOP Publishing Ltd. In this paper, we propose a new face hallucination technique, face images reconstruction in HSV color space with a semi-orthogonal multilinear principal component analysis method. This novel hallucination technique can perform directly from tensors via tensor-to-vector projection by imposing the orthogonality constraint in only one mode. In our experiments, we use facial images from FERET database to test our hallucination approach which is demonstrated by extensive experiments with high-quality hallucinated color faces. The experimental results assure clearly demonstrated that we can generate photorealistic color face images by using the SO-MPCA subspace with a linear regression model.