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Improving the Recognition of Occluded Faces by Means of Two-dimensional Orthogonal Projection into Local Subspaces

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Image Analysis and Recognition (ICIAR 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9164))

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Abstract

The paper presents a problem of reducing the influence of natural occlusion on face recognition accuracy. It is based on transformation (two-dimensional Karhunen-Loeve Transform) of face parts into local subspaces calculated by means of two-dimensional Principal Component Analysis and two-dimensional Linear Discriminant Analysis. We use a sequence of operations consisting of face scale and orientation normalization and individual facial regions extraction. Independent recognitions are performed on extracted facial regions and their results are combined in order to perform a final classification. The experiments on images taken from publicly available datasets show that such a simple algorithm is able to successfully recognize faces without high computational overhead, in contrast to more sophisticated methods presented recently. In comparison to typical, whole-face-based approach, developed method gives significantly better accuracy.

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Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Żołnierska Str. 52, 71–210, Szczecin, Poland

    Paweł Forczmański & Piotr Łabȩdź

Authors
  1. Paweł Forczmański
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  2. Piotr Łabȩdź
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Corresponding author

Correspondence to Paweł Forczmański .

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Editors and Affiliations

  1. University of Waterloo, Waterloo, Ontario, Canada

    Mohamed Kamel

  2. University of Porto, Porto, Portugal

    Aurélio Campilho

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Forczmański, P., Łabȩdź, P. (2015). Improving the Recognition of Occluded Faces by Means of Two-dimensional Orthogonal Projection into Local Subspaces. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2015. Lecture Notes in Computer Science(), vol 9164. Springer, Cham. https://doi.org/10.1007/978-3-319-20801-5_25

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  • DOI: https://doi.org/10.1007/978-3-319-20801-5_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20800-8

  • Online ISBN: 978-3-319-20801-5

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