Journal of South China University of Technology (Natural Science Edition) ›› 2013, Vol. 41 ›› Issue (11): 16-22.doi: 10.3969/j.issn.1000-565X.2013.11.003

• Electronics, Communication & Automation Technology • Previous Articles     Next Articles

Three- Dimension Face Recognition Based on Information Fusion

Liao Guang- jun1,2 Zeng Wei1 Liu Yu1,2 Li Zhi- fu2,3 Hu Yue- ming1,2   

  1. 1.School of Automation Science and Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China;2.Engineering Research Center for Precision Electronic Manufacturing Equipments of the Ministry of Education,South ChinaUniversity of Technology,Guangzhou 510640,Guangdong,China; 3.School of Mechanical and Automotive Engineering,SouthChina University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2013-05-24 Revised:2013-08-09 Online:2013-11-25 Published:2013-10-11
  • Contact: 李致富(1981-)，男，博士后，助理研究员，主要从事智能材料驱动控制研究工作． E-mail:sundylzf@gmail.com
  • About author:廖广军(1981- )，男，博士生，主要从事模式识别的应用研究． E-mail:gdliaogj@gmail．com
  • Supported by:

    国家“863” 计划项目 (2012AA041312);国家自然科学基金资助项目(61203060);公安部应用创新课题(2012YYCXGDST081);2013 年广东省省级科技计划项目;华南理工大学中央高校基本科研业务费专项资金资助项目(2013ZM0098);广东警官学院院级重点项目(2011- Z02)

PDF

543

Abstract:

In order to overcome the disadvantages of two- dimension face recognition,a three- dimension methodusing a Kinect instrument is proposed based on the information fusion.In this method,for the face detection,theeyes' location is used to locate the face,and the skin color model as well as the depth information is employed torealize the face filtering.For the face recognition,the DTW (Dynamic Time Warping) algorithm is applied to therapid extraction of the face contour,and an improved LBP (Local Binary Pattern) matching algorithm is proposed,in which the weight value distribution is determined by analyzing the color image information and the face physiolo-gical characteristics.Experimental results show that the proposed method for face recognition is applicable and is ofimproved real- time capability and robustness.

Key words:  face detection, three- dimension face recognition, information fusion, dynamic time warping, localbinary pattern matching

CLC Number: