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Recognition Oriented Feature Hallucination for Low Resolution Face Images

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Advances in Multimedia Information Processing - PCM 2016 (PCM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9917))

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Abstract

In face recognition, Low Resolution (LR) images will lead to the decline of the recognition rate. In this paper, we propose a novel recognition oriented feature hallucination method to map the features of a LR facial image to its High Resolution (HR) version. We extract the principal component analysis (PCA) features of LR and HR face images. Then, canonical correlation analysis is applied to establish the coherent subspaces between the PCA features of the LR and HR face images. Furthermore, a recognition rate guided prediction model is proposed to map the LR features to the HR version, which is employed an adaptive Piecewise Kernel Partial Least Squares (P-KPLS) predictor. Finally, a weighted combination of the hallucinated PCA features and the Local Binary Pattern Histogram (LBPH) features are adopted for face recognition. Experimental results show that the proposed method has a superior recognition rate.

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Acknowledgments

The work in this paper is supported by the National Natural Science Foundation of China (No. 61471013, No. 61531006, No. 61372149 and No. 61370189), the Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions (No. CIT&TCD201404043, CIT&TCD20150311), the Beijing Natural Science Foundation (No. 4142009, No. 4163071), the Science and Technology Development Program of Beijing Education Committee (No. KM201510005004, No. KM201410005002), Funding Project for Academic Human Resources Development in Institutions of Higher Learning under the Jurisdiction of Beijing Municipality.

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Authors and Affiliations

  1. Signal and Information Processing Lab, Beijing University of Technology, Beijing, China

    Guangheng Jia, Xiaoguang Li, Li Zhuo & Li Liu

Authors
  1. Guangheng Jia
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  2. Xiaoguang Li
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  3. Li Zhuo
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  4. Li Liu
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Corresponding author

Correspondence to Xiaoguang Li .

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Editors and Affiliations

  1. Zhengzhou University, Zhengzhou, China

    Enqing Chen

  2. Jiaotong University, Xi’an, China

    Yihong Gong

  3. Zhengzhou University, Zhengzhou, China

    Yun Tie

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Jia, G., Li, X., Zhuo, L., Liu, L. (2016). Recognition Oriented Feature Hallucination for Low Resolution Face Images. In: Chen, E., Gong, Y., Tie, Y. (eds) Advances in Multimedia Information Processing - PCM 2016. PCM 2016. Lecture Notes in Computer Science(), vol 9917. Springer, Cham. https://doi.org/10.1007/978-3-319-48896-7_27

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  • DOI: https://doi.org/10.1007/978-3-319-48896-7_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48895-0

  • Online ISBN: 978-3-319-48896-7

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