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Deep CNN-Based Face Recognition

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Synonyms

Face identification; Face recognition; Face verification

Definition

Automatic face recognition is the problem of identifying a person from an image or a video. The problem of face recognition can be divided into face identification and face verification. The standard approach for training a CNN for solving these problems include four steps: face detection, alignment, representation, and classification (Fig. 1). Identification is the problem of assigning an identity to an image from a list of identities. From another perspective, this can be considered as trying to retrieve the best matching face from a gallery for a given probe image. On the other hand, face verification involves verifying whether two face images are of the same person. This is usually performed by computing the similarity between feature representations of the two faces. Both identification and verification have benefited immensely from developments in deep learning algorithms and more advanced CNN...

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Acknowledgements

This research is based upon work supported by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via IARPA R&D Contract No. 2014-14071600012.

Author information

Authors and Affiliations

  1. University of Maryland, College Park, MD, USA

    Ankan Bansal, Carlos D. Castillo & Rama Chellappa

  2. Department of Computer Science, University of Maryland, College Park, MD, USA

    Carlos D. Castillo

  3. Amazon, Seattle, WA, USA

    Rajeev Ranjan

Authors
  1. Ankan Bansal
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  2. Rajeev Ranjan
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  3. Carlos D. Castillo
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  4. Rama Chellappa
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Corresponding author

Correspondence to Ankan Bansal .

Section Editor information

  1. University of Maryland, College Park, United States

    Rama Chellappa

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Bansal, A., Ranjan, R., Castillo, C.D., Chellappa, R. (2020). Deep CNN-Based Face Recognition. In: Computer Vision. Springer, Cham. https://doi.org/10.1007/978-3-030-03243-2_880-1

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  • DOI: https://doi.org/10.1007/978-3-030-03243-2_880-1

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