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Lip Reading Based on Sampled Active Contour Model

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Image Analysis and Recognition (ICIAR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3656))

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Abstract

This paper describes a model-based method for detecting lip region from image sequences. Our approach is by Sampled Active Contour Model (S-ACM). The original S-ACM has the problem which can’t expand. To overcome this problem, we propose the elastic S-ACM. Moreover, based on the extracted lip contour, the effective delta radius features are fed to the word HMM. We recorded ten words that uses for the wheelchair control, and obtained a recognition rate of 89% with twelve features.

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References

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Author information

Authors and Affiliations

  1. Dept. of Electrical and Electronic Engineering, Tottori University, 4-101 Koyama, Tottori, 680-8552, Japan

    Takeshi Saitoh & Ryosuke Konishi

Authors
  1. Takeshi Saitoh
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  2. Ryosuke Konishi
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Editor information

Editors and Affiliations

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

    Mohamed Kamel

  2. FEUP - Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, P.O. Box, 4200-465, Porto, Portugal

    Aurélio Campilho

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© 2005 Springer-Verlag Berlin Heidelberg

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Saitoh, T., Konishi, R. (2005). Lip Reading Based on Sampled Active Contour Model. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2005. Lecture Notes in Computer Science, vol 3656. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11559573_63

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  • DOI: https://doi.org/10.1007/11559573_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29069-8

  • Online ISBN: 978-3-540-31938-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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