A new strategy for 3D face recognition

被引：0

作者：

Liu, Xinrong ^{[1
]}

Yang, Guang ^{[2
]}

Sun, Xiangbin ^{[2
]}

机构：

[1] Department of Computer, Shandong Institute of Business and Technology, Yantai

[2] Engineering Training Center, Yantai University, Yantai

来源：

Journal of Information and Computational Science | 2015年 / 12卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Face recognition; Improved; Recognition; Registration; Template face;

D O I：

10.12733/jics20105863

中图分类号：

学科分类号：

摘要：

This paper discusses the improved method for 3D face recognition. The novel method is introduced in detail. By the Thin Plate Spline (TPS) transformation, the negative effects caused by expressions and postures are weakened. In order to reduce the time for registration, the template face is used for the process of registration. After a series of registration process, the point set distance is calculated. The face that with the smallest point set distance to the query face is selected as the final recognition result. The method for the temp template face acquiring and the method for registration are improved. To reserve the original face feature to a large extent, the temp template face is selected from the original face set, and some registration is directly processed between the template face and original face set. Experiment results show that the new method of this paper has better identification rate and higher operating efficiency. Copyright © 2015 Binary Information Press.

引用

页码：2759 / 2768

页数：9

共 17 条

[1]

Lu X.G., Jain A.K., Deformation modeling for robust 3D face matching, IEEE Transactions on Pattern Analysis and Machine Intelligence, 30, 8, pp. 1346-1356, (2008)

[2]

Xu C., Li S., Tan T., Quan L., Automatic 3D face recognition from depth and intensity Gabor features, Pattern Recognition, 42, 9, pp. 1895-1905, (2009)

[3]

Efrsty B., Bilgazyev E., Shah S., Profile-based 3D aided face recognition, Pattern Recognition, 45, 1, pp. 43-63, (2012)

[4]

Du S.Y., Zheng N.N., Scaling iterative closest point algorithm for registration of M-D point sets, Journal of Visual Communication and Image Representation, 21, 5, pp. 442-452, (2010)

[5]

Tang H., Yin B., Sun Y., 3D face recognition using local binary patterns, Signal Processing, 93, 8, pp. 2190-2198, (2012)

[6]

Hesher C., Srivastava A., Erlebacher G., A novel technique for face recognition using range imaging, Proceedings of Symposium on Signal Processing and Its Applications, pp. 201-204, (2003)

[7]

Pan G., Wu Z., 3D face recognition from range data, International Journal of Image and Graphics, 5, 3, pp. 573-583, (2005)

[8]

Irfanoglu M.O., Gokberk B., Akarun L., 3D shape-based face recognition using automatically registered facial surfaces, The 17th International Conference on Pattern Recognition, pp. 183-186, (2004)

[9]

Bookstein F.L., Principal warps: Thin-plate splines and the decomposition of deformations, IEEE Transactions on Pattern Analysis and Machine Intelligence, 11, 6, pp. 567-585, (1989)

[10]

Lu X., Jain A.K., Deformation modeling for robust 3D race matching, IEEE Transactions on Pattern Analysis and Machine Intelligence, 30, 8, pp. 1346-1357, (2008)

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