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Intelligent Video Event Analysis and Understanding pp 155–194Cite as

Real-Time Face Recognition from Surveillance Video

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 332))

Abstract

This chapter describes an experimental system for the recognition of human faces from surveillance video. In surveillance applications, the system must be robust to changes in illumination, scale, pose and expression. The system must also be able to perform detection and recognition rapidly in real time.

Our system detects faces using the Viola-Jones face detector, then extracts local features to build a shape-based feature vector. The feature vector is constructed from ratios of lengths and differences in tangents of angles, so as to be robust to changes in scale and rotations in-plane and out-of-plane. Consideration was given to improving the performance and accuracy of both the detection and recognition steps.

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Author information

Authors and Affiliations

  1. School of Electronics, Electrical Engineering and Computer Science, Queens University Belfast, Belfast, BT7 1NN, UK

    Michael Davis, Stefan Popov & Cristina Surlea

Authors
  1. Michael Davis
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  2. Stefan Popov
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  3. Cristina Surlea
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Editor information

Editors and Affiliations

  1. School of Computing, University of Dundee , DD1 4HN, Dundee, Scotland, UK

    Jianguo Zhang

  2. Department of Electronic & Electrical Engineering, The University of Sheffield, S1 3JD, Sheffield, UK

    Ling Shao

  3. Microsoft Research Asia , 49 Zhichun Road, 100190, Beijing, P.R. China

    Lei Zhang

  4. Digital Imaging Research Centre, Faculty of Computing, Information Systems and Mathematics, Kingston University, Penrhyn Road, Kingston upon Thames, KT1 2EE, Surrey, UK

    Graeme A. Jones

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© 2011 Springer-Verlag Berlin Heidelberg

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Davis, M., Popov, S., Surlea, C. (2011). Real-Time Face Recognition from Surveillance Video. In: Zhang, J., Shao, L., Zhang, L., Jones, G.A. (eds) Intelligent Video Event Analysis and Understanding. Studies in Computational Intelligence, vol 332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17554-1_8

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  • DOI: https://doi.org/10.1007/978-3-642-17554-1_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17553-4

  • Online ISBN: 978-3-642-17554-1

  • eBook Packages: EngineeringEngineering (R0)

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