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Evaluation of Face Recognition Systems

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Deep Learning-Based Face Analytics

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

While face recognition research has been perennial and popular since its inception, there has been a marked escalation in this research in recent years due to the confluence of several factors, primarily the development of advanced machine learning algorithms, free and robust software implementations thereof, ever faster GPU processors for running them, vast web-scraped face image databases, open performance benchmarks, and a vibrant face recognition literature.

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Authors and Affiliations

  1. National Institute of Standards and Technology, Gaithersburg, USA

    Patrick Grother & Mei Ngan

Authors
  1. Patrick Grother
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  2. Mei Ngan
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Corresponding author

Correspondence to Patrick Grother .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University at Buffalo-SUNY, Buffalo, NY, USA

    Nalini K Ratha

  2. Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA

    Vishal M. Patel

  3. Departments of Electrical and Computer Engineering (Whiting School of Engineering) and Biomedical Engineering (School of Medicine), Johns Hopkins University, Baltimore, MD, USA

    Rama Chellappa

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Grother, P., Ngan, M. (2021). Evaluation of Face Recognition Systems. In: Ratha, N.K., Patel, V.M., Chellappa, R. (eds) Deep Learning-Based Face Analytics. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-030-74697-1_17

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  • DOI: https://doi.org/10.1007/978-3-030-74697-1_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-74696-4

  • Online ISBN: 978-3-030-74697-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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