A Hybrid Algorithm of Facial Feature Point Location Based on Improved MR-ASM and AAM

机译：基于改进MR-ASM和AAM的人脸特征点定位混合算法

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摘要

Accurate and robust location of feature point is a difficult and complicated issue in face recognition. This paper proposes a facial feature point location algorithm based on improved Multi-Resolution- Active Shape Models (MR-ASM) and Active Appearance Models (AAM). There are three main achievements of our algorithm: 1, we unify MR-ASM and AAM together to improve facial feature point location. 2, AAM is improved so that it has the same implementation framework as ASM. 3, the MR-ASM is adjusted to figure out more robust parameters. Experimental results prove that our algorithm is more accurate than traditional MR-ASM.

机译：特征点的准确和鲁棒定位是人脸识别中一个困难而复杂的问题。本文提出了一种基于改进的多分辨率主动形状模型（MR-ASM）和主动外观模型（AAM）的面部特征点定位算法。我们的算法有三个主要成就：1，我们将MR-ASM和AAM结合在一起以改善面部特征点的位置。 2，改进了AAM，使其具有与ASM相同的实现框架。参照图3，调整MR-ASM以找出更可靠的参数。实验结果证明我们的算法比传统的MR-ASM更加准确。

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来源
《International Conference on Signal Processing(ICSP'06); 20061116-20; Guilin(CN)》|2006年|P.1831-1834|共4页
会议地点 Guilin(CN)
作者
Zhang Sicong; Wu Lifang; He Xiaoguang; Tian Jie;
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作者单位

School of Electronic Information and control Engineering, Beijing University of Technology, Beijing, China, 100022;

Key Lab. of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, P.O.Box 2728, Beijing 100080 Ch;

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原文格式 PDF
正文语种 eng
中图分类通信理论;
关键词
MR-ASM; AAM; location of facial feature point;

机译：MR-ASM; AAM;面部特征点定位;

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A Hybrid Algorithm of Facial Feature Point Location Based on Improved MR-ASM and AAM

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