应用梯度矢量流Snake和灰预测的人脸轮廓跟踪

周志宇; 杨卫成; 汪亚明; 张建新; 郑磊

doi:10.3788/OPE.20111911.2744

您当前的位置：

首页 >

文章列表页 >

应用梯度矢量流Snake和灰预测的人脸轮廓跟踪

信息科学 | 更新时间：2020-08-12

- 应用梯度矢量流Snake和灰预测的人脸轮廓跟踪
- Realization of face contour tracking by GVF Snake and grey prediction
- 光学精密工程 2011年19卷第11期页码：2744-2752
- 作者机构：
  
  1. 浙江理工大学信息电子学院,浙江杭州,310018
  2. 浙江理工大学机械与自动控制学院,浙江杭州,310018
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目(No.60873020,No.61070063)();浙江省自然科学基金资助项目 (No. Y1090256, No.Z1080702)()
- DOI：10.3788/OPE.20111911.2744
  中图分类号： TP391.4-4
- 收稿日期：2011-05-09，
  
  修回日期：2011-06-21，
  
  网络出版日期：2011-11-25，
  
  纸质出版日期：2011-11-25
- 稿件说明：
移动端阅览
周志宇, 杨卫成, 汪亚明, 张建新, 郑磊. 应用梯度矢量流Snake和灰预测的人脸轮廓跟踪[J]. 光学精密工程, 2011,19(11): 2744-2752

ZHOU Zhi-yu, YANG Wei-cheng, WANG Ya-ming, ZHANG Jian-xin, ZHENG Lei. Realization of face contour tracking by GVF Snake and grey prediction[J]. Editorial Office of Optics and Precision Engineering, 2011,19(11): 2744-2752
周志宇, 杨卫成, 汪亚明, 张建新, 郑磊. 应用梯度矢量流Snake和灰预测的人脸轮廓跟踪[J]. 光学精密工程, 2011,19(11): 2744-2752 DOI： 10.3788/OPE.20111911.2744.

ZHOU Zhi-yu, YANG Wei-cheng, WANG Ya-ming, ZHANG Jian-xin, ZHENG Lei. Realization of face contour tracking by GVF Snake and grey prediction[J]. Editorial Office of Optics and Precision Engineering, 2011,19(11): 2744-2752 DOI： 10.3788/OPE.20111911.2744.

摘要

为了提高动态图像序列中人脸轮廓跟踪时梯度矢量流(GVF)Snake算法的实时性

同时解决人脸跟踪中的遮挡问题

提出了GVF Snake和单变量一阶灰色模型GM(1

1)相结合的人脸轮廓提取方法。该方法首先利用人脸运动信息和肤色模型粗略地检测出运动人脸轮廓

然后采用GVF Snake算法将人脸轮廓精确地提取出来

从而有效解决GVF Snake算法的初始化问题。根据人脸轮廓运动的整体性

利用GM(1

1)模型预测人脸轮廓质心的位置

并以预测位置作为GVF Snake的迭代依据

同时将GVF Snake提取的人脸轮廓质心位置作为下一帧图像GM(1

1)模型的预测依据。存在遮挡时

则以GM(1

1)模型预测保持跟踪的连续性。实验结果表明

该算法跟踪的平均时间仅为GVF Snake算法的8.0%

平均跟踪误差仅为GVF Snake算法的31.2%

而且能更好地反映人脸轮廓的运动规律

跟踪实时性强

鲁棒性好。

Abstract

In order to improve the real-time performance of the Gradient Vector Flow Snake(GVF Snake) algorithm for face contour tracking in a dynamic image sequence and to overcome the occlusion problem in face tracking

a novel image extraction method combining the GVF Snake algorithm and the single variable first-order grey model GM(1

1) is proposed to extract the face contour. In this method

the moving face contour is roughly detected out firstly by using human motion information and the skin-color model

and then the accurate face contour is extracted by using the GVF Snake algorithm

by which the initialization problem of the GVF Snake algorithm is solued. For the integrity feature of face contour motion

the GM(1

1) model is used to predict the centroid position of face contour and then the position is used as the iteration basis of the GVF Snake algorithm. Meanwhile

the centroid position of face contour extracted with GVF Snake is taken as the prediction basis of the GM(1

1) model for the next frame. When the occlusion exists

the continuity of tracking can be held with the prediction of GM(1

1) model. Experimental results show that by proposed method

the average tracking time and the average tracking error are only 8.0% and 31.2% of those of the GVF Snake algorithm respectively. It can be concluded that this method can better reflect the motion law of face contour

and has strong real-time performance and good robustness.

关键词

Keywords

references

TSAI C Y, DUTOIT X, SONG K T, et al.. Robust face tracking control of a mobile robot using self-tuning Kalman filter and echo state network [J]. Asian Journal of Control, 2010, 12(4): 488-509.[2] YE J H, LIU ZH G, ZHANG J. A face tracking algorithm based on LBP histograms and particle filtering . International Conference on Natural Computation, 2010(7): 3550-3553.[3] BULBUL A, CIPILOGLU Z, CAPIN T. A color-based face tracking algorithm for enhancing interaction with mobile devices [J]. Visual Computer, 2010, 26(5):311-323.[4] LUKASZ A S, RAUL V G. Identity recognition-based correction mechanism for face tracking . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, 6169: 203-212.[5] 段其昌,周奇,段盼. 结合水平集和粒子滤波的人脸轮廓跟踪[J]. 光电工程, 2010,37(3):117-121. DUAN Q CH, ZHOU Q, DUAN P. Face contour tracking by combing level set method and particle filtering [J]. Opto-Electronic Engineering, 2010, 37(3):117-121. (in Chinese)[6] CHANG J S, KIM E Y, KIM H J. Facial boundary detection with an active contour model [J]. Pattern Recognition Letters, 2007, 28(1): 64-74.[7] 黄福珍,苏剑波. 基于Level Set 方法的人脸轮廓提取与跟踪[J]. 计算机学报,2003,26(4):491-496. HUANG F ZH , SU J B. Face contour extraction and tracking using level sets [J]. Chinese Journal of Computers, 2003,26(4):491-496. (in Chinese)[8] KASS M, WITKIN A. Snakes: Active contour models [J]. International Journal of Computer Vision, 1987, 1(4): 321-331.[9] XU CH Y, PRINCE J L. Snakes, shapes, and gradient vector flow [J]. IEEE Trans on Image Processing, 1998, 7(3): 359-369.[10] BRESSON X, ESEDOGLU S. Fast global minimization of the active contour/snake model [J]. Journal of Mathematical Imaging and Vision, 2007, 28(2):151-167.[11] 范延滨,刘彩霞,贾世宇,等. GVF Snake 模型中初始轮廓线设置算法的研究[J]. 中国图象图形学报, 2008,13(1): 58-63. FAN Y B, LIU C X, JIA SH Y, et al.. The research of contour initialization algorithm in GVF snake model [J]. Journal of Image and Graphics, 2008, 13(1): 58-63. (in Chinese)[12] 颜佳,吴敏渊,陈淑珍,等. 跟踪窗口自适应的Mean Shift跟踪[J]. 光学精密工程,2009,17(10):2606-2611. YAN J, WU M Y ,CHEN SH ZH, et al.. Mean shift tracking with adaptive tracking window [J]. Opt. Precision Eng., 2009,17(10):2606-2611. (in Chinese)[13] 孙中森,孙俊喜,宋建中,等. 一种抗遮挡的运动目标跟踪算法[J]. 光学精密工程,2007,15(2):268-272. SUN ZH S, SUN J X, SONG J ZH, et al.. Anti-occlusion arithmetic for moving object tracking [J].Opt. Precision Eng., 2007, 15 (2): 268-272. (in Chinese)[14] 邓聚龙. 灰色系统基本方法[M].2版. 武汉:华中科技大学出版社 , 2005. DENG J L. A primary methods of grey system theory[M]. 2nd ed. Wuhan: Huazhong Universityof Science and Technology Press, 2005. (in Chinese)[15] COMANICIU D, RAMESH V, MEER P. Kernel-based object tracking [J]. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2003, 25(5):564-577.

浏览量

512

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

暂无数据