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Face Recognition by Cortical Multi-scale Line and Edge Representations

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Image Analysis and Recognition (ICIAR 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4142))

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Abstract

Empirical studies concerning face recognition suggest that faces may be stored in memory by a few canonical representations. Models of visual perception are based on image representations in cortical area V1 and beyond, which contain many cell layers for feature extraction. Simple, complex and end-stopped cells provide input for line, edge and keypoint detection. Detected events provide a rich, multi-scale object representation, and this representation can be stored in memory in order to identify objects. In this paper, the above context is applied to face recognition. The multi-scale line/edge representation is explored in conjunction with keypoint-based saliency maps for Focus-of-Attention. Recognition rates of up to 96% were achieved by combining frontal and 3/4 views, and recognition was quite robust against partial occlusions.

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Author information

Authors and Affiliations

  1. Escola Superior de Tecnologia, Campus da Penha

    João Rodrigues

  2. Vision Laboratory, University of Algarve, Campus de Gambelas – FCT, 8000-117, Faro, Portugal

    J. M. Hans du Buf

Authors
  1. João Rodrigues
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  2. J. M. Hans du Buf
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Editor information

Editors and Affiliations

  1. Faculty of Engineering, Institute of Biomedical Engineering, Rua Dr. Roberto Frias, University of Porto, 4200-465, Porto, Portugal

    Aurélio Campilho

  2. Electrical and Computer Engineering Department, University of Waterloo,  

    Mohamed Kamel

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© 2006 Springer-Verlag Berlin Heidelberg

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Rodrigues, J., du Buf, J.M.H. (2006). Face Recognition by Cortical Multi-scale Line and Edge Representations. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2006. Lecture Notes in Computer Science, vol 4142. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11867661_30

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  • DOI: https://doi.org/10.1007/11867661_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44894-5

  • Online ISBN: 978-3-540-44896-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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