基于层次模型和融合决策的多姿态人脸识别技术

朱长仁; 王润生

基于层次模型和融合决策的多姿态人脸识别技术

计量
- 文章访问数: 2189
- HTML全文浏览量: 141
- PDF下载量: 626
- 被引次数: 0
出版历程
- 收稿日期: 2001-03-30
- 修回日期: 2001-08-17
- 刊出日期: 2002-11-19

Multi-pose face recognition based on a hierarchical model and fusion decision

摘要

摘要: 该文提出了基于层次模型和融合决策的多姿态人脸识别技术,它首先把各人脸按姿态分成几个大类,并且对各大类按人脸个体分成相应子类,然后对各个大类分别进行基于特征脸的人脸识别,最后对各个姿态的人脸识别中间结果进行融合决策得到真正的人脸识别结果,该算法同时也提供了其姿态识别结果,并且大大减小了耗时,该文算法对ORL,UMIST,Stirling数据和一些自拍数据共1200幅人脸图像进行了识别测试实验,其结果令人鼓舞。
- 人脸识别; 多姿态; 特征脸; 多视图; 层次模型; 融合决策
Abstract: A multi-pose face recognition algorithm based on a hierarchical model and fusion decision is proposed in the paper. First, face images are divided into several classes based on their poses and every class into many sub-classes based on their subjects. Then, traditional face recognition technology based on eigenface is applied in the process of face recognition in every class. Finally, fusion decision is adopted to get the final result of face recognition based on the intermediate result of every class. It also, can get the result of its pose recognition and its computation time is far less than that of the traditional methods. The algorithm discussed above has been tested in the experiments of a multi-pose face database with total 100 subjects and 1200 face images, which consists of ORL, UMIST, Stirling and face database of authors lab. The results are encouraging.

HTML全文

参考文献(1)

R. Chellappa, C. L. Wilson, S. Sirohey, Human and machine recognition of faces: A survey, Proc.IEEE., 1995, 83(5), 705-740.[2]A. Samal, P. A. Iyengar, Automatic recognition and analysis of human faces and facial expressions:A survey, Pattern Recognition, 1992, 25(1), 65-77.[3]D. Valentin, H. Abdi, A. J. OToole, G. W. Cottrel, Connectionist model of face processing: A survey, Pattern Recognition, 1994, 27(9), 1209-1230.[4]R. Brunelli, T. Poggio, Face recognition: Feature versus templates, IEEE Trans. on PAMI., 1993,PAMI-15(10), 1042-1052.[5]S. ranganath, Face recognition using transform features and neural networks, Pattern Recognition,1997, 30(10), 1615-1622.[6]Lam Kin-Man, Yan Hong, An analytical-to-holistic approach for face recognition based on a single frontal views, IEEE Trans. on PAMI., 1998, PAMI-20(7), 673-686.[7]M. Turk, A. Pentland, Eigenfaces for recognition, Journal of Cognitive Neuroscience, 1991, 3(1),71-86.[8]A. Pentland.[J].B. Moghaddam, T. Starner, View-based and modular eigenspaces for face recognition, IEEE Conf. CVPR94, Seattle.1994,:-[9]K.M. Lam.[J].H. Yan, An improved method for locating and extracting the eye in human face images, ICPR96, Vienna, Austria.1996,:-[10]X. Xie, R. Sudhaker, H. Zhuang, On improving eye feature extraction using deformable templates,Pattern Recognition, 1994, 27(6), 791-799.

施引文献

资源附件(0)

访问统计