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Texture-Constrained Shape Prediction for Mouth Contour Extraction and its State Estimation
 

Summary: Texture-Constrained Shape Prediction for Mouth Contour Extraction and its
State Estimation
Zhaorong LI, Haizhou AI
Computer Science and Technology Department, Tsinghua University, Beijing 100084, China
E-mail: ahz@mail.tsinghua.edu.cn
Abstract
In this paper, we present an automatic mouth
contour and state estimation system. An efficient mouth
contour extraction algorithm is proposed under the
framework of Active Shape Model (ASM). Considering
large mouth shape variations, we propose a texture-
constrained shape prediction method for initialization.
To improve accuracy and robustness of classical ASM,
we use classifiers trained by Real AdaBoost to
characterize the local texture model. This model is
proved to have much stronger discriminative power
than Gaussian model of classical ASM. After
extracting the mouth contour, the mouth is classified
into one of 4 typical states by Support Vector Machine
(SVM) based on the shape parameter. Experiments

  

Source: Ai, Haizhou - Department of Computer Science and Technology, Tsinghua University

 

Collections: Computer Technologies and Information Sciences