[1]许进文,赵启军,陈虎. 一种改进的三维局部约束模型初始化方法[J].计算机技术与发展,2017,27(01):30-33.
　XU Jin-wen,ZHAO Qi-jun,CHEN Hu. An Improved Initialization Method for 3 D Constrained Local Model[J].,2017,27(01):30-33.
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 一种改进的三维局部约束模型初始化方法(/HTML)
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年01期
页码:
30-33
栏目:
智能、算法、系统工程
出版日期:
2017-01-10

文章信息/Info

Title:
 An Improved Initialization Method for 3 D Constrained Local Model
文章编号:
1673-629X（2017)01-0030-04
作者:
 许进文; 赵启军; 陈虎
 四川大学 视觉合成图形图像技术国防重点学科实验室
Author(s):
 XU Jin-wen; ZHAO Qi-jun; CHEN Hu
关键词:
 ; 三维人脸特征点定位; 三维局部约束模型; 初始化; 鲁棒级联姿态回归
Keywords:
 ; 3D facial landmark localization; 3D Constrained Local Model ( CLM-Z); initialization; Robust Cascaded Pose Regression ( RCPR)
分类号:
TP391.4
文献标志码:
A
摘要:
 三维局部约束模型(3D Constrained Local Model,CLM-Z)算法,综合利用灰度和深度信息检测三维人脸数据中的特征点(如眼角、鼻尖和嘴角),实现了较高的检测精度。 CLM-Z方法一般使用人脸位置和平均三维人脸模型进行初始化。设计了四个实验定量地分析CLM-Z参数初始化对算法精度的影响：在BU-4DFE库上评估CLM-Z算法精度；通过平移人脸边界框扰动平移参数的初始值；通过缩放人脸边界框扰动尺度参数的初始值；通过给定绕y轴和z轴的旋转角扰动旋转参数的初始值。实验结果表明,CLM-Z算法可容忍平移扰动约为人脸宽的1/6,在(0.75,1.50)缩放范围内算法精度不会下降,可容忍y轴和z轴旋转角约20°。基于以上评估结果,进一步提出在纹理图像上检测特征点作为初始化,然后再进行CLM-Z迭代。在BU-4DFE数据库上的评估结果证明,该初始化方法能有效提升CLM-Z方法的特征点定位精度。
Abstract:
 3D Constrained Local Model (CLM-Z) achieves high accuracy in detecting 3D facial landmarks (e. g. , eye corners,nose tip and mouth corners) via taking full advantage of both intensity and depth information. CLM-Z is conventionally initialized based on the location of face and mean 3D facial model. The effect of CLM-Z initialization on detection accuracy is evaluated quantitively by carrying out the following experiments:assessing the accuracy of CLM-Z with the conventional initialization method on the BU-4DFE database, translating the face to perturb the initial value of translation parameter,varying the size of detected face to perturb the initial value of scale parameter,varying the rotation angles around y-axis and z-axis to perturb the initial value of rotation parameter. Experimental results show that CLM-Z can tolerate translations up to approximately 1/6 of the width of the face,scalings between 0. 75 and 1. 50,and rota-tions within 20 degrees. Based on the above evaluation results,a novel initialization method is proposed further that exploits facial land-marks detected firstly on 2D texture images. Experiments on the BU-4DFE database show that the proposed initialization method can suc-cessfully improve the 3D landmark localization accuracy of CLM-Z approach.

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更新日期/Last Update: 2017-04-01