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Towards an Efficient Facial Image Compression with Neural Networks

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Image Analysis and Processing – ICIAP 2022 (ICIAP 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13231))

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Abstract

Digital images are more and more part of everyday life. Efficient compression methods are needed to reduce the disk-space usage for their storage and the bandwidth for their transmission while keeping the resolution and the visual quality of the reconstructed images as close to the original images as possible. Not all images have the same importance. The facial images are being extensively used in many applications (e.g., law enforcement, social networks) and require high efficient facial image compression schemes in order to not compromise face recognition and identification (e.g., for surveillance and security scenarios). For this reason, we propose a promising approach that consists of a custom loss that combines the two tasks of image compression and face recognition. The results show that our method compresses efficiently face images guaranteeing high perceptive quality and face verification accuracy.

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Notes

  1. 1.

    This acronym is a file format for LZMA archives.

  2. 2.

    It is available here https://github.com/timesler/facenet-pytorch.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Catania, Catania, Italy

    Maria Ausilia Napoli Spatafora, Alessandro Ortis & Sebastiano Battiato

Authors
  1. Maria Ausilia Napoli Spatafora
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  2. Alessandro Ortis
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  3. Sebastiano Battiato
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Corresponding author

Correspondence to Maria Ausilia Napoli Spatafora .

Editor information

Editors and Affiliations

  1. Boston University, Boston, MA, USA

    Stan Sclaroff

  2. National Research Council, Lecce, Italy

    Cosimo Distante

  3. National Research Council, Lecce, Italy

    Marco Leo

  4. University of Catania, Catania, Italy

    Giovanni M. Farinella

  5. Technische Universität München, Garching, Germany

    Federico Tombari

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Napoli Spatafora, M.A., Ortis, A., Battiato, S. (2022). Towards an Efficient Facial Image Compression with Neural Networks. In: Sclaroff, S., Distante, C., Leo, M., Farinella, G.M., Tombari, F. (eds) Image Analysis and Processing – ICIAP 2022. ICIAP 2022. Lecture Notes in Computer Science, vol 13231. Springer, Cham. https://doi.org/10.1007/978-3-031-06427-2_43

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  • DOI: https://doi.org/10.1007/978-3-031-06427-2_43

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  • Online ISBN: 978-3-031-06427-2

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