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Real Time Segmentation of Lip Pixels for Lip Tracker Initialization

  • Mohammad Sadeghi
  • Josef Kittler
  • Kieron Messer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2124)

Abstract

We propose a novel segmentation method for real time lip tracker initialisation which is based on a Gaussian mixture model of the pixel data. The model is built using the Predictive Validation technique advocated in [4]. In order to construct an accurate model in real time, we adopt a quasi-random image sampling technique based on Sobol sequences. We test the proposed method on a database of 145 images and demonstrate that its accuracy, even with a few number of samples, is satisfactory and significantly better than the segmentation obtained by k-means clustering. Moreover, the proposed method does not require the number of segments to be specified a priori.

Keywords

gaussian mixture modelling lip tracking 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Mohammad Sadeghi
    • 1
  • Josef Kittler
    • 1
  • Kieron Messer
    • 1
  1. 1.Centre for Vision, Speech and Signal Processing School of Electronics, Computing and MathematicsUniversity of SurreyGuildfordUK

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