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(Lip Recognition Using Active Shape Model and Gaussian Mixture Model)  

장경식 (동의대학교 멀티미디어공학과)
이임건 (동의대학교 영화영상공학과)
Publication Information
Journal of KIISE:Software and Applications / v.30, no.5_6, 2003 , pp. 454-460 More about this Journal
Abstract
In this paper, we propose an efficient method for recognizing human lips. Based on Point Distribution Model, a lip shape is represented as a set of points. We calculate a lip model and the distribution of shape parameters using Principle Component Analysis and Gaussian mixture, respectively. The Expectation Maximization algorithm is used to determine the maximum likelihood parameter of Gaussian mixture. The lip contour model is derived by using the gray value changes at each point and in regions around the point and used to search the lip shape in a image. The experiments have been performed for many images, and show very encouraging result.
Keywords
lip recognition; principle component analysis; expectation maximization algorithm;
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