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Face Alignment Models

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Book cover Handbook of Face Recognition

Abstract

In order to interpret images of faces (e.g., for recognition), it is important to have a model of the different ways that a face may appear. Though faces vary widely, changes can be broken down into two categories—changes in shape and changes in the texture (patterns of pixel values) across the face—that are largely due to differences between individuals, but also due to changes in expression, viewpoint and lighting conditions. In this chapter, we describe a powerful method of generating compact models of shape and texture variation, and describe two methods—the Active Shape Model (ASM) and Active Appearance Model (AAM)—that fit an appearance model to an unseen image of the face so that we can interpret its underlying properties (e.g., identity).

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Acknowledgements

The authors would like to thank their numerous colleagues who have contributed to the research summarised in this chapter, including C. Beeston, F. Bettinger, D. Cooper, D. Cristinacce, G. Edwards, A. Hill, J. Graham, H. Kang, P. Kittipanya-ngam and M. Roberts.

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Authors and Affiliations

  1. Imaging Science and Biomedical Engineering, University of Manchester, Manchester, UK

    Phil Tresadern, Tim Cootes, Chris Taylor & Vladimir Petrović

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  1. Phil Tresadern
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  2. Tim Cootes
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  4. Vladimir Petrović
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Correspondence to Tim Cootes .

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Editors and Affiliations

  1. Institute of Automation, Center Biometrics Research & Security, Chinese Academy of Science, Room 1227, Zhongguancun 95, Beijing Donglu, 100080, China, People's Republic

    Stan Z. Li

  2. Dept. Computer Science & Engineering, Michigan State University, East Lansing, 48824-1226, Michigan, USA

    Anil K. Jain

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Tresadern, P., Cootes, T., Taylor, C., Petrović, V. (2011). Face Alignment Models. In: Li, S., Jain, A. (eds) Handbook of Face Recognition. Springer, London. https://doi.org/10.1007/978-0-85729-932-1_5

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  • DOI: https://doi.org/10.1007/978-0-85729-932-1_5

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