Extraction of Visual Features for Lipreading
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In this paper, we propose a new method based on lip motion sequence and the Unconstrained Minimum Average Correlation Energy (UMACE) filter as a classifier for person identification. UMACE filter has advantages in terms of their characteristics such as distortion-tolerant, shift-invariant and high discrimination ability. Therefore, executing UMACE filter provides an ideal application for person identification because we deal with the variations of the lip appearance in each frame sequence. The results obtained using a Digit Database show that the use of lip motion sequence and UMACE filter offer a good potential and can be an alternative technique for a person identification system.