首页 | 本学科首页   官方微博 | 高级检索  
     

基于局部形状图的三维人脸特征点自动定位
引用本文:王蜜宫,陈锻生,林超.基于局部形状图的三维人脸特征点自动定位[J].计算机应用,2010,30(5):1255-1258.
作者姓名:王蜜宫  陈锻生  林超
作者单位:1. 国立华侨大学计算机科学与技术学院2. 福建省华侨大学计算机系3. 厦门大学 软件学院
基金项目:福建省自然科学基金资助项目(2009J01289);;福建省科技计划国际合作重点项目(2008I0021)
摘    要:准确定位人脸特征控制点是三维人脸识别的关键技术之一。提出了一种新的三维人脸特征点自动定位方法,结合局部形状索引与基于局部形状图(LSM)的统计模型,通过误差分析自适应地确定局部形状图的统计半径,实现任意姿态下的三维人脸鼻尖和内眼角的自动精确定位。在CASIA 3D人脸数据库的比较实验结果表明,该方法比基于先验信息和基于曲率分析的定位方法都具有更高的定位精确度。

关 键 词:特征点定位    形状索引    曲度    局部形状图    支持向量机
收稿时间:2009-10-30
修稿时间:2009-12-22

Automatic location of 3D facial feature points based on local shape map
WANG Mi-gong,CHEN Duan-sheng,LIN Chao.Automatic location of 3D facial feature points based on local shape map[J].journal of Computer Applications,2010,30(5):1255-1258.
Authors:WANG Mi-gong  CHEN Duan-sheng  LIN Chao
Affiliation:1.College of Computer Science and Technology/a>;Huaqiao University/a>;Quanzhou Fujian 362021/a>;China/a>;2.College of Software/a>;Xiamen University/a>;Xiamen Fujian 351006/a>;China
Abstract:Accurate location of face feature points is one of the key steps in 3D face recognition.A fully automatic locating algorithm for 3D facial nose tip and inner eye corner in different views was presented,which relied on a statistical model combining Local Shape Map (LSM) and local shape index,and the statistical radius of the local shape map was adaptively determined by error analysis.The experimental results on the CASIA 3D face database demonstrate that this method performs more precise location than heuris...
Keywords:feature point location                                                                                                                        shape index                                                                                                                        curvedness                                                                                                                        Local Shape Map (LSM)                                                                                                                        Support Vector Machine (SVM)
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《计算机应用》浏览原始摘要信息
点击此处可从《计算机应用》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号