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Dissimilarity Representations for Low-Resolution Face Recognition

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Similarity-Based Pattern Recognition (SIMBAD 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9370))

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Abstract

Low-resolution face recognition is a very difficult problem. In this setup, the training database or gallery contains high-resolution images, but the image to be recognized is of low resolution. Thus we are dealing with a resolution mismatch problem for training and test images. Standard face recognition methods fail in this setting, which suggests that current feature representation approaches are not adequate to cope with this problem. Therefore, we propose the use of dissimilarity representations based on different strategies, which differ in how images with different resolutions are compared, to solve the resolution mismatch problem. Experiments on four standard face datasets demonstrate that a strategy based on first down-scaling and afterwards up-scaling training images while up-scaling test images outperforms all the other approaches.

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Authors and Affiliations

  1. Advanced Technologies Application Center, La Habana, Cuba

    Mairelys Hernández-Durán & Yenisel Plasencia-Calaña

  2. Biomedical Imaging Group Rotterdam, Erasmus Medical Center, Rotterdam, The Netherlands

    Veronika Cheplygina

  3. Pattern Recognition Laboratory, Delft University of Technology, Delft, The Netherlands

    Veronika Cheplygina & Yenisel Plasencia-Calaña

Authors
  1. Mairelys Hernández-Durán
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  2. Veronika Cheplygina
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  3. Yenisel Plasencia-Calaña
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Corresponding author

Correspondence to Mairelys Hernández-Durán .

Editor information

Editors and Affiliations

  1. University of Copenhagen, Copenhagen, Denmark

    Aasa Feragen

  2. DAIS, Università Ca' Foscari Venezia, Venezia Mestre, Italy

    Marcello Pelillo

  3. Delft University of Technology, Delft, Zuid-Holland, The Netherlands

    Marco Loog

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Hernández-Durán, M., Cheplygina, V., Plasencia-Calaña, Y. (2015). Dissimilarity Representations for Low-Resolution Face Recognition. In: Feragen, A., Pelillo, M., Loog, M. (eds) Similarity-Based Pattern Recognition. SIMBAD 2015. Lecture Notes in Computer Science(), vol 9370. Springer, Cham. https://doi.org/10.1007/978-3-319-24261-3_6

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  • DOI: https://doi.org/10.1007/978-3-319-24261-3_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24260-6

  • Online ISBN: 978-3-319-24261-3

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