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Active Shape Model and Its Application to Face Alignment

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Subspace Methods for Pattern Recognition in Intelligent Environment

Part of the book series: Studies in Computational Intelligence ((SCI,volume 552))

Abstract

Active Shape Model (ASM) is a model-based method, which makes use of a prior model of what is expected in the image, and typically attempts to find the best match position between the model and the data in a new image. It has been successfully applied to many problems and we apply ASM to the face recognition. We represent all shapes with a set of landmarks to form a Point Distribution Model (PDM) respectively. After landmarks alignment and Principal Component Analysis, we construct gray-level profile for each landmark in all multi-resolution versions of a training image. In search procedure, we give the model’s position an initial estimate. We adopt a lot of improvements to the classical ASM, such as increasing the width of search profile to reduce the effect of noise, grouping landmarks to avoid mouth shape distort in the search procedure and altering the direction of search profile.

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Author information

Authors and Affiliations

  1. School of Electronic and Information Engineering, Dalian University of Technology, Dalian, China

    Huchuan Lu

  2. Department of Computer Science, University of Maryland, College Park, USA

    Fan Yang

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  1. Huchuan Lu
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  2. Fan Yang
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Editors and Affiliations

  1. Ritsumeikan University College of Science & Engineering, Kusuatsu, Shiga, Japan

    Yen-Wei Chen

  2. Faculty of Education, Science, Technology & Mathematics, University of Canberra, Canberra, South Australia, Australia

    Lakhmi C. Jain

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Lu, H., Yang, F. (2014). Active Shape Model and Its Application to Face Alignment. In: Chen, YW., C. Jain, L. (eds) Subspace Methods for Pattern Recognition in Intelligent Environment. Studies in Computational Intelligence, vol 552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54851-2_1

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  • DOI: https://doi.org/10.1007/978-3-642-54851-2_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54850-5

  • Online ISBN: 978-3-642-54851-2

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