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Lip Contour Segmentation Using Kernel Methods and Level Sets

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Advances in Visual Computing (ISVC 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4842))

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Abstract

This paper proposes a novel method for segmenting lips from face images or video sequences. A non-linear learning method in the form of an SVM classifier is trained to recognise lip colour over a variety of faces. The pixel-level information that the trained classifier outputs is integrated effectively by minimising an energy functional using level set methods, which yields the lip contour(s). The method works over a wide variety of face types, and can elegantly deal with both the case where the subjects’ mouths are open and the mouth contour is prominent, and with the closed mouth case where the mouth contour is not visible.

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George Bebis Richard Boyle Bahram Parvin Darko Koracin Nikos Paragios Syeda-Mahmood Tanveer Tao Ju Zicheng Liu Sabine Coquillart Carolina Cruz-Neira Torsten MĂĽller Tom Malzbender

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© 2007 Springer-Verlag Berlin Heidelberg

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Khan, A., Christmas, W., Kittler, J. (2007). Lip Contour Segmentation Using Kernel Methods and Level Sets. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76856-2_9

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  • DOI: https://doi.org/10.1007/978-3-540-76856-2_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-76855-5

  • Online ISBN: 978-3-540-76856-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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