Please wait a minute...
J4  2011, Vol. 45 Issue (1): 30-36    DOI: 10.3785/j.issn.1008-973X.2011.01.005
计算机技术﹑电信技术     
基于三维模型与Gabor小波的人脸特征点跟踪方法
战江涛1,2,刘强3,柴春雷1
1.浙江大学 计算机科学与技术学院,浙江 杭州 310027; 2.浙江机电职业技术学院 设计艺术系,浙江 杭州 310053;
3.清华大学 美术学院,北京 100084
Facial feature tracking using three-dimensional model and
Gabor wavelet
ZHAN Jiang-tao1,2, LIU Qiang3, CHAI Chun-lei1
1.College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China;2.Department of
Design and Art, Zhejiang Institute of Mechanical and Electrical Engineering, Hangzhou 310053, China;
3. Academy of Arts and Design, Tsinghua University, Beijing 100084, China
 全文: PDF  HTML
摘要:

为了实现人脸特征点跟踪系统的鲁棒性和精确性,使用光束平差法模型将基于三维人脸几何模型的跟踪方法与基于Gabor小波的特征点跟踪方法结合起来,提出基于三维模型与Gabor小波的人脸特征点跟踪方法.该方法使用基于Gabor小波的特征跟踪方法来得到每帧的初始特征点,使用基于三维人脸几何模型的整合优化跟踪方法来得到每帧的最终特征点.与3类典型人脸特征点跟踪方法的对比实验结果表明,该方法克服了以往方法基于二维图像信息来寻找特征点的局限性,可以实现鲁棒的、实时的、大角度的人脸特征点跟踪.

Abstract:

A new facial feature points tracking scheme was proposed by integrating three-dimensional geometric face modelbased tracking method and facial feature points tracking method with Gabor wavelet in bundle adjustment way in order to realize the robustness and accuracy of facial tracking system. The tracking method with Gabor wavelet was used to get the initial feature points. Then the model-based tracking method was used to get the final optimal feature points. The scheme overcame the disadvantage of using two-dimensional image features compared with three other typical methods. The scheme can be used for robust, real-time and wide-angle facial feature tracking.

出版日期: 2011-03-03
:  TP 391.41  
基金资助:

国家自然科学基金资助项目(60703041);中央高校基本科研业务费专项资金资助项目(2009QNA5014).

通讯作者: 柴春雷, 男, 副教授.     E-mail: dishengchai@126.com
作者简介: 战江涛(1977-), 男, 山东莱州人, 博士生, 从事人机工程研究. E-mail: sdzhanjt@163.com
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  

引用本文:

战江涛,刘强,柴春雷. 基于三维模型与Gabor小波的人脸特征点跟踪方法[J]. J4, 2011, 45(1): 30-36.

ZHAN Jiang-tao, LIU Qiang, CHAI Chun-lei. Facial feature tracking using three-dimensional model and
Gabor wavelet. J4, 2011, 45(1): 30-36.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2011.01.005        http://www.zjujournals.com/eng/CN/Y2011/V45/I1/30

[1] 金城,卜佳俊,陈华,等. 自底向上的人脸特征点定位[J]. 浙江大学学报:工学版,2008, 42(5): 794-799.
JIN Cheng, BU Jiajun, CHEN Hua, et al. Human face detection and feature tracking in a bottomup way [J]. Journal of Zhejiang University:Engineering Science, 2008, 42(5): 794-799.
[2] COOTES T, WALKER K, TAYLOR C. Viewbased active appearance models [C] ∥Proceedings of 4th IEEE International Conference on Automatic Face and Gesture Recognition. Grenoble, French: IEEE, 2000: 227-232.
[3] HOU X, LI S, ZHAN G H, et al. Direct appearance models [C] ∥Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR′01). Hawaii: IEEE, 2001: 828-833.
[4] ROGERIO S, FERIS A, ROBERTO M, et al. Tracking facial features using Gabor wavelet networks [C]∥Proceedings of XIII Brazilian Symposium on Computer Graphics and Image Processing. Gramado: IEEE, 2000: 22-27.
[5] 李英,赖剑煌,阮邦志. 多模板ASM方法及其在人脸特征点检测中的应用[J]. 计算机研究与发展, 2007, 41(1): 133-140.
LI Ying, LAI Jianhuang, RUAN Bangzhi. Multitemplate ASM and its application in facial feature points detection [J]. Journal of Computer Research and Development, 2007, 41(1): 133-140.
[6] 段鸿,程义民,王以孝,等. 基于KanadeLucasTomasi算法的人脸特征点跟踪方法[J]. 计算机辅助设计与图形学学报,2004, 16(3): 279-283.
DUAN Hong, CHENG Yimin, WANG Yixiao, et al. Tracking facial feature points using KanadeLucasTomasi approach [J]. Journal of ComputerAided Design and Computer Graphics, 2004, 16(3): 279-283.
[7] 颜蒋国,潘立登. 基于Gabor小波的人脸特征点跟踪方法[J]. 计算机应用,2004, 24(7): 50-51.
YAN Jiangguo, PAN Lideng. Tracking facial feature with Gabor wavelet [J]. Computer Applications, 2004, 24(7): 50-51.
[8] WISKOTT L, FELLOUS J M, KRUGER N, et al. Face recognition by elastic bunch graph matching [J]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 1997, 19(7): 775-779.
[9] VACCHETTI L, LEPETIT V, FUA P. Stable realtime 3d tracking using online and offline information [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(10): 1385-1391.
[10] VIOLA P, JONES M. Rapid object detection using a boosted cascade of simple features [C]∥Proceedings of 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR′01). Hawaii: IEEE, 2001: 511-518.
[11] DEMENTHON D F, DAVIS L S. Modelbased object pose in 25 lines of code [J]. International Journal of Computer Vision, 1995, 15(1/2): 123-141.
[12] DAUGMAN J G. Twodimensional spectral analysis of cortical receptive field profiles [J]. Vision Research, 1980, 20(10): 847-856.
[13] VACCHETTI L, LEPETIT V, FUA P. Fusing online and offline information for stable 3d tracking in realtime [C]∥ Proceedings of 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR′03). Wisconsin: IEEE, 2003: 241-248.
[14] Cross correlation [EB/OL]. http:∥en.wikipedia.org/wiki/Crosscorrel ation#Normalized_crosscorrelation. [2009-05-31].
[15] TRIGGS B, MCLAUCHLAN P, HARTLEY R, et al. Bundle adjustment: a modern synthesis [C]∥ Proceedings of International Workshop on Vision Algorithms (ICCV′99). Kerkyra: IEEE, 1999: 298-372.
[16] WILLIAM H P, BRIAN P F, SAUL A T, et al. C数值算法[M]. 傅祖芸,赵梅娜,丁岩石,译. 2版. 北京:电子工业出版社, 2004: 121-128.
[17] LEE K C, HO J, YANG M H, et al. Visual tracking and recognition using probabilistic appearance manifolds [J]. Computer Vision and Image Understanding, 2005, 99(3): 303-331.
[18] 宋刚,艾海舟,徐光佑. 纹理约束下的人脸特征点跟踪[J]. 软件学院, 2004, 15(11): 1607-1615.
SONG Gang, AI Haizhou, XU Guangyou. Texture constrained facial point tracking [J]. Journal of Software, 2004, 15(11): 1607-1615.
[19] COOTES T F, WHEELER G V, WALKER K N, et al. Viewbased active appearance models [J]. Image Vision Computing, 2002, 20(9): 657-664.
[20] TONG Yan, WANG Yang, ZHU Zhiwei, et al. Robust facial feature tracking under varying face pose and facial expression [J]. Pattern Recognition, 2007, 40(11): 3195-3208.
[21] ROMDHANI S, GONG S, PSARROU A. Multiview nonlinear active shape model using kernel PCA [C]∥Proceedings of BMVC. Nottingham: IEEE, 1999: 483-492.

[1] 杨玉婷, 史玉回, 夏顺仁. 基于讨论机制的头脑风暴优化算法[J]. J4, 2013, 47(10): 1705-1711.
[2] 朱晓恩, 郝欣, 夏顺仁. 基于Levy flight的特征选择算法[J]. J4, 2013, 47(4): 638-643.
[3] 孙创日,甄帅,夏顺仁. 基于吸引区域的多模态脑磁共振图像仿射配准[J]. J4, 2012, 46(9): 1722-1728.
[4] 谢迪, 童若锋, 唐敏, 冯阳. 具有高区分度的视频火焰检测方法[J]. J4, 2012, 46(4): 698-704.
[5] 戴渊明, 韦巍, 林亦宁. 基于颜色纹理特征的均值漂移目标跟踪算法[J]. J4, 2012, 46(2): 212-217.
[6] 李启雷, 金文光, 耿卫东. 基于无线惯性传感器的人体动作捕获方法[J]. J4, 2012, 46(2): 280-285.
[7] 刘晨彬,潘颖,张海石,黄峰平,夏顺仁. 基于磁共振图像的脑瘤MGMT表达状况检测算法[J]. J4, 2012, 46(1): 170-176.
[8] 钱诚, 张三元. 适用于目标跟踪的加权增量子空间学习算法[J]. J4, 2011, 45(12): 2240-2246.
[9] 曹颖, 郝欣, 朱晓恩, 夏顺仁. 基于自动随机游走的乳腺肿块分割算法[J]. J4, 2011, 45(10): 1753-1760.
[10] 吕谷来, 李建平, 李锵, 俞利兴, 朱松明, 楼建忠, 袁祎琳. 基于机器视觉的砧木定位识别方法[J]. J4, 2011, 45(10): 1766-1770.
[11] 赖小波,朱世强. 基于互相关信息的非参数变换立体匹配算法[J]. J4, 2011, 45(9): 1636-1642.
[12] 刘建明, 鲁东明, 葛蓉. 基于全局优化的图像修复及其在GPU上实现[J]. J4, 2011, 45(2): 247-252.
[13] 王金德, 寿黎但, 李晓燕, 陈刚. 基于多重分割捆绑特征的目标图像检索[J]. J4, 2011, 45(2): 259-266.
[14] 梁文锋,项志宇. 鲁棒的PTZ摄像机目标跟踪算法[J]. J4, 2011, 45(1): 59-63.
[15] 宋坤坡, 夏顺仁, 徐清. 考虑小波系数相关性的超声图像降噪算法[J]. J4, 2010, 44(11): 2203-2208.