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A Two-Directional Two-Dimensional PCA Correlation Filter in the Phase only Spectrum for Face Recognition in Video

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Video Analytics. Face and Facial Expression Recognition and Audience Measurement (VAAM 2016, FFER 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10165))

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Abstract

This paper presents a novel hybrid two-directional, two-dimensional Principal Component Analysis based correlation filter for face recognition. This hybrid (2D)\(^2\)PCA-correlation filter is capable of simultaneously dealing with several uncontrolled factors that are present in video surveillance cameras making it difficult to properly recognize faces. Such factors are addressed by linking (2D)\(^2\)PCA in the Fourier domain with correlation filters (CFs) to speed up the process of video-based face recognition. The former method helps to extract and to represent more efficiently the facial features using the original image matrices, while the later method is used to simultaneously handle illumination variations, expression, partial occlusions and spatial shifts. An exploration of the capabilities of this novel method is performed using the Yale-B, AR, and YouTube face databases, showing an improvement in face recognition despite using a subspace of smaller dimensionality.

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Notes

  1. 1.

    A pre-whitening step is performed to yield a phase-only spectrum with a unity magnitude for all spatial frequencies (u, v).

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Acknowledgments

This work is supported by the National Science and Technology Council of Mexico (CONACyT), project #215546, scholarship #328839; and INAOE.

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Authors and Affiliations

  1. Instituto Nacional de Astrofísica, Óptica y Electrónica, Luis Enrique Erro 1, Tonantzintla, 72840, Puebla, Mexico

    Víctor E. Alonso, Rogerio Enríquez-Caldera & L. Enrique Sucar

Authors
  1. Víctor E. Alonso
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  2. Rogerio Enríquez-Caldera
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  3. L. Enrique Sucar
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Corresponding author

Correspondence to Víctor E. Alonso .

Editor information

Editors and Affiliations

  1. Aalborg University, Aalborg, Denmark

    Kamal Nasrollahi

  2. Institute of Applied Sciences and Intelligent Systems, Lecce, Italy

    Cosimo Distante

  3. Stevens Institute of Technology, Hoboken, New Jersey, USA

    Gang Hua

  4. Queen Mary University of London, London, United Kingdom

    Andrea Cavallaro

  5. Aalborg University, Aalborg, Denmark

    Thomas B. Moeslund

  6. Università di Catania, Catania, Italy

    Sebastiano Battiato

  7. Rensselaer Polytechnic Institute, Troy, New York, USA

    Qiang Ji

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Alonso, V.E., Enríquez-Caldera, R., Sucar, L.E. (2017). A Two-Directional Two-Dimensional PCA Correlation Filter in the Phase only Spectrum for Face Recognition in Video. In: Nasrollahi, K., et al. Video Analytics. Face and Facial Expression Recognition and Audience Measurement. VAAM FFER 2016 2016. Lecture Notes in Computer Science(), vol 10165. Springer, Cham. https://doi.org/10.1007/978-3-319-56687-0_7

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  • DOI: https://doi.org/10.1007/978-3-319-56687-0_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56686-3

  • Online ISBN: 978-3-319-56687-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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